Stanford University’s Global AI Vibrancy Tool ranked Canada fifth of 29 countries, and third among G7 nations, in artificial intelligence (AI) research, development and economy in 2021. Research and development metrics used include research grants, publications and citations, while economic metrics include private investment funding, newly funded AI companies, skill penetration and talent concentration.
Artificial Intelligence and Its Potential Impact on Canadian Society
AI broadly refers to the ability of computers to replicate human intelligence, such as identifying patterns and making predictions and decisions. AI encompasses several techniques, but one of the most discussed is machine learning. Machine learning is a method of using large data sets to make predictions that improve over time and with more data.
AI has become increasingly integrated into the day-to-day life of many Canadians, such as through navigation devices, targeted advertisements and smart device personal assistants.
A 2021 poll of Canadians’ views on AI found that the surveyed population generally had a positive outlook on the likely impact of AI on society. However, the results varied by application sector, with few believing AI would positively impact arts and culture or law enforcement.
Meanwhile, a 2020 Statistics Canada paper exploring the risk of automation-related job transformation and potential for job loss found that approximately 10% of Canadian workers were at high risk of automation-related job transformation. While the paper did not specify the proportion of this transformation linked to AI, the latter is included within the broader categorization of automation-related job transformation. The risk was not distributed evenly across different demographic factors, individual characteristics and employment sectors. Workers associated with a higher risk included those:
- aged 55 or older;
- with no postsecondary credentials;
- with low employment income;
- employed part-time;
- employed in small firms; and
- employed in certain occupations or sectors (e.g., office support, manufacturing).
Federal Support for Artificial Intelligence Research in Canada
The Pan-Canadian Artificial Intelligence Strategy
In March 2017, Canada became the first country to launch a national AI strategy in the form of the Pan-Canadian AI Strategy (the Strategy). The Strategy provided $125 million in funding with the objective of developing a Canadian AI community. The Strategy is linked to:
- the recruitment of over 100 researchers as part of the Canadian Institute for Advanced Research’s AI Chair program;
- an annual graduating class of over 200 master’s and Ph.D. students from Canada’s three national AI institutes:
- the Alberta Machine Intelligence Institute (Amii) in Edmonton;
- Mila – Quebec Artificial Intelligence Institute in Montréal; and
- the Vector Institute for Artificial Intelligence in Toronto;
- the launch of over 50 multinational companies with AI research and development laboratories in Canada; and
- the launch of over 900 AI start-ups across Canada and $1.5 billion in venture funding raised by Canadian AI start-ups in 2021.
Phase 2 of the Strategy, announced in Budget 2021, provides $443.8 million in funding over 10 years starting in 2021–2022. It prioritizes commercializing and adopting AI technology, increasing computing capacity and infrastructure, developing AI standards, and advancing AI for health, energy and the environment.
The application of gender-based analysis plus to Budget 2021’s renewal of the strategy revealed that AI workforce demographics tend towards highly educated, higher-income men from urban regions.
Global Innovation Clusters
The Global Innovation Clusters, formerly Innovation Superclusters, were launched in 2017 by Innovation, Science and Economic Development Canada to increase research collaboration and enhance Canada’s technological and commercialization capabilities. Among these clusters, the Digital Technology Cluster and the Scale AI Cluster are working to advance AI research, including projects related to AI-powered training, supply chains and logistic management. According to the Scale AI Annual Report 2021–2022, Scale AI projects are expected to create over 4,000 jobs and generate over $9 billion in economic value by 2030.
Other Federal Artificial Intelligence Research Initiatives
Other federal research initiatives related to AI can be found in the tri-agency funding programs – the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council of Canada, and the Social Sciences and Humanities Research Council. For example, the tri-agencies have funded collaborative projects with the United Kingdom on AI and projects linking AI, health and society in Canada.
Other federal departments and organizations, including the National Research Council of Canada (NRC) and the Public Health Agency of Canada (PHAC), have also funded AI-related research programs and projects, such as NRC’s Artificial Intelligence for Design Challenge program and a PHAC pilot study on detecting suicide-related behaviour through AI analysis of social media data.
Implications for Federal Policies and Programs
Legislation and Frameworks for the Governance of Artificial Intelligence
In Canada, AI development and applications fall under both federal and provincial jurisdiction. For example, jurisdiction over privacy, data protection, health and human rights is shared between the federal and provincial governments; competition law and intellectual property law are within federal jurisdiction; and consumer protection law and property law – including trade secret law – are within provincial jurisdiction.
Bill C-27, An Act to enact the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act and the Artificial Intelligence and Data Act and to make consequential and related amendments to other Acts is currently at second reading in the House of Commons and aims to address AI explicitly as it relates to federal jurisdiction.
If enacted, the Artificial Intelligence and Data Act portion of Bill C-27 would require those responsible for high-impact AI systems to fulfill certain obligations, including establishing measures to identify, assess and mitigate the risks of harm or biased output that could result from the use of AI.
The potential for bias in AI derives from the quality of the data sets used to formulate AI-powered predictions and decisions. Data sets can introduce bias through a sample that does not reflect the population or situation to which it applies, or through the replication of prior biased decision-making. For example, predictive policing algorithms can result in a high police presence in racialized communities that have historically experienced over-policing.
Some countries and international organizations have adopted legislation or established other tools to address bias in AI research and encourage the development of responsible and trustworthy AI systems. They include the European Union’s Artificial Intelligence Act, the Montréal Declaration for a Responsible Development of Artificial Intelligence Development, the European Commission’s Ethics Guidelines for Trustworthy AI and the Organisation for Economic Co-operation and Development AI Policy Observatory’s values-based principles.
Role of the Parliament of Canada
AI has implications across many dimensions of Canadian federal legislation and policy areas. Senate and House of Commons committees have studied AI in relation to various policy areas and specific uses of the technology to date, including:
- the October 2022 report by the House of Commons Standing Committee on Access to Information, Privacy and Ethics, Facial Recognition Technology and the Growing Power of Artificial Intelligence;
- the Senate Standing Committee on Transport and Communications’ January 2018 report, Driving Change: Technology and the future of the automated vehicle; and
- the Senate Standing Committee on Social Affairs, Science and Technology’s October 2017 report, Challenge Ahead: Integrating Robotics, Artificial Intelligence and 3D Printing Technologies into Canada’s Healthcare Systems.
Other policy areas that may be impacted by advances in AI research include:
- AI applications in national security and intelligence;
- the use of automated decision making in the processing of immigration and refugee applications;
- balancing of data linkage, sharing and transparency components of AI development with privacy considerations;
- the environmental impacts of AI;
- the application of AI to public health and population health decision making, including pandemic management;
- the implications of AI for employment, including the automation of certain jobs and sectors;
- ensuring human rights, equity and inclusion are supported within AI systems; and
- AI and automated decision making in the public service (the Treasury Board Directive on Automated Decision-Making).
Brookfield Institute. Intro to AI for Policymakers: Understanding the shift, March 2018.
Government of Canada Advisory Council on Artificial Intelligence. Annual reports.
International Development Research Centre. Artificial intelligence and human development: Toward a research agenda, April 2018.
Smith, Matthew and Sujaya Neupane. “Artificial intelligence, digital technology and advanced production.” The Digitalisation of Science, Technology and Innovation: Key Developments and Policies. Organisation for Economic Co‑operation and Development, 11 February 2020.
Statistics Canada. Machine learning: An introduction, 3 May 2021.
Thomas, Nye, Erin Chochla, and Susie Lindsay. Regulating AI: Critical Issues and Choices. Law Commission of Ontario, April 2021.
By Kelsey Brennan, Library of Parliament