成人大片 researchers influence $2.4B government funding plan to maintain Canada鈥檚 AI advantage
A recent report from The Dais at 成人大片 informed a major government investment plan to build AI compute capacity and maintain Canada鈥檚 global AI leadership advantage. Image by vecstock on Freepik.
Major U.S. tech giants like Microsoft, Amazon and Google have been making headlines recently for their significant investments in nuclear power. The reason? To meet the electricity demands of the energy-intensive computing needs of artificial intelligence (AI).
Energy is just one aspect of the massive infrastructure needs required to build and test sophisticated AI algorithms and support data-heavy workloads of AI and machine learning. This critical issue is highlighted in a March 2024 report released by , a public policy and leadership think tank at 成人大片. The research centre is helping to lead research on improved public policies for the artificial intelligence economy.
The report, , is Canada鈥檚 first public independent policy paper on the country鈥檚 insufficient AI computing capacity (AIC). It outlines the ways the Canadian government should invest in AIC to maintain Canada鈥檚 global leadership potential in AI development and innovation.
In an April 2024 , The Dais authors senior economist Graham Dobbs and senior advisor Jake Hirsch-Allen, explain that while Canada is a leader in AI research and talent, increased support for the development of AI infrastructure is critical to harnessing the economic potential of this new technology while also addressing Canada鈥檚 lagging productivity.
鈥淏y addressing infrastructure needs鈥攑hysical components like servers and computing processing units鈥攚e increase the capacity to build and test complex AI algorithms which allow for innovation in training and developing sophisticated AI systems,鈥� says Hirsch-Allen.
In fact, The Dais researchers explain, compared to its G7 peers, Canada holds the lowest amount of publicly available computing infrastructure and performance, which they warn will impact the country鈥檚 global competitiveness and the future health of the economy.
Recent research from The Dais shows that the United States has 90 times more raw computing power than Canada. Adjusting for population and size of the economy, it has 7.6 times more than Canada; Italy has 9 times more. Japan leads by approximately 8 times and France and Germany by 2 to 3 times.
In their policy brief, Dobbs and Hirsch-Allen explain, 鈥淸Canada鈥檚] AI Compute gap could hinder Canadian innovators from growing successful AI firms, slow down businesses鈥� adoption of AI technologies, and limit researchers鈥� advancement of the next generation of AI inquiry.鈥�
The researchers also explain the risk posed to Canada鈥檚 economic and data sovereignty.
"The threat to Canadian data and economic sovereignty in 2025 cannot be stressed enough,鈥� says Dobbs. 鈥淲ithout the sovereign capacity to protect, evaluate, and innovate domestic data assets, there is a risk to national security. Economically, looming trade and economic sanctions pressure Canadian workers, innovators, and businesses to increase productivity and create opportunity without the reliance on foreign digital and computing infrastructure. Investing in Canada's AI compute infrastructure will be critical to unlocking domestic economic growth and opportunity."
The Dais Senior Economist Graham Dobbs (left) researches educational and technological innovations in the Canadian labour force and its impact on occupational distributions and transitions. The Dais fellow Jake Hirsch-Allen's work focuses on inclusive technology and skills, responsible tech and AI governance.
AI report informs major federal government funding commitment
, along with two concrete proposals on improving Canada鈥檚 AI economy鈥攖o effect.
In April 2024, the . The Dais policy brief directly helped to inform federal government programs supporting AI research, commercialization and expanded infrastructure access for startups, researchers and government.
鈥淎I requires more processing power than any software to date and often requires very specific processing chips. In April 2024, Canada announced $2.4 billion in funding under the broad title of 鈥榗ompute鈥�, which is the processing power necessary to power AI. How this funding is disbursed will determine the impact of this investment鈥�
As Hirsch-Allen explains, AIC funding could entail building new data centres, expanding current Canadian data centres or the use of hyperscalers offered by Google, Amazon, Microsoft to expand cloud computing capacity.
鈥淭his means funding could subsidize big U.S. tech companies,鈥� he points out. 鈥淚 think part of the big debate is the question of why the Canadian government would be diverting funds to big American companies, except that they are the only ones that are providing the compute capacity required by Canadian companies.鈥�
These are among the critical issues that require creative problem-solving and solutions around distribution of capital.
Sustainable AI development
The environmental impact of AI is also a vital consideration in developing computational infrastructure. Significant energy and water resources are required for AI operations. The report addresses some of this, highlighting the need for clean energy sources and the strategic placement of data centres to minimize environmental harm.
鈥淨uebec and British Columbia have some of the cleanest electricity in the world,鈥� says Hirsch-Allen. 鈥淟argely hydro, unlike Ontario or for the rest of the country. The cleanliness and portability of these energy sources holds real capacity-building potential for these provinces.鈥�
Fostering inclusive prosperity
Government funding for AI will also support its adoption and regulation, including ensuring inclusive access to this transformative technology to maximize its benefits for broader society, rather than allowing it to be concentrated in the private sector, a recommendation underscored in The Dais report.
In a recent Dobbs and Hirsch-Allen assert that supporting equitable access to AI infrastructure and services must begin with extensive public consultation. It鈥檚 important to consult with diverse sectors of society, particularly groups and organizations traditionally marginalized in tech innovation, such as people with disabilities, nonprofits and cultural organizations.
Ideally, Hirsch-Allen explains, funding would build Canadian AIC capacity and access to better support these organizations and research institutions, startups and small and medium-sized businesses.
鈥淭he pan-Canadian AI strategy has already built one of the richest and most productive [innovation] ecosystems in the world, except the benefits aren't filtering down to the average Canadian,鈥� says Hirsch-Allen. 鈥淚 am personally most invested in ensuring the average Canadian worker, whether a mechanic at a garage or a teacher in a classroom, can be positively impacted by this transformational Gen AI gold rush, and benefit in the long term from Canada鈥檚 major investments strategies.鈥�
And, with more voices at the table, AI鈥檚 development can move away from reinforcing biases, discrimination and inequities related to gender, race and class, ensuring more inclusive data sets and algorithms.
鈥淐anada鈥檚 approach should focus on creating infrastructure and policies that foster inclusive prosperity, ensuring that the benefits of AI extend across the entire spectrum of society.鈥�
The allocation of resources towards responsible AI development will be a continuing focus of research for The Dais. With its expertise in economics and productivity, the centre plays a critical role in studying how these advancements can benefit a diverse range of citizens, and offer insights and recommendations to help bridge the digital divide.
For more research on AI and the Canadian economy, find the latest published research from The Dais here: