Opportunities, Risks, and Regulation of AI in Canada’s Strategic Industries

Witness:
Dr. James Elder
Professor & York Research Chair in Human and Computer Vision
Director, Centre for AI & Society
Department of Electrical Engineering & Computer Science, Lassonde School of Engineering
Department of Psychology, Faculty of Health
¿ì²¥ÊÓƵ
Toronto, ON

Opening Statement:

INTRODUCTION:

Thank you for this opportunity to appear before the committee. My expertise is in computational neuroscience, computer vision, AI and robotics. I have been a professor at York for 30 years and have led many collaborative research projects with industry and public sector partners. I am now serving as Director of the ¿ì²¥ÊÓƵ Centre for AI & Society (CAIS), which unites 74 research faculty members across 7 different university faculties engaged in all dimensions of AI research.

OPPORTUNITIES:

AI offers enormous opportunities for Canadian industry. Canadian researchers have been leaders in developing core principles underpinning current AI technologies. In the last several years, attention has shifted to large language models (LLMs) developed by hyperscalers like OpenAI, Google and Anthropic. We are now in a new phase in which these AI models, including LLMs, can transform a myriad of industry processes and create new businesses. Importantly, these opportunities to businesses at all scales from small to large.

Promising applications include:

• Drone-based AI for construction process management
• Robotics for healthcare and senior care
• Computer vision and AI for urban mobility
• Business process automation

The Government of Canada can help Canadians to seize these opportunities in a number of ways:

• Lead by example: Use Canadian AI technologies to improve processes in all branches of government.
• Support post-secondary AI application research and training: Establish capital programs in partnership with provincial governments to establish new high-profile facilities for collaborative research on AI applications and training.
• Catalyze collaborative research: Establish pan-Canadian pre-competitive collaborative applied research networks focused on the application of AI in specific domains, e.g., healthcare, robotics, mobility, business processes.
• Dual and civilian use. Support R&D for both dual-use and civilian applications of AI

RISKS:

As a disruptive technology, AI poses many risks.

• Missing out. If Canada does not rapidly embrace the efficiencies and novel opportunities of AI, we risk becoming uncompetitive in global markets and less able to provide the services that Canadians cherish.
• Employment shifts. There will be large shifts in labour markets, including contractions in some areas and expansions in others. Workers will need to adapt their skillsets and workflow to make productive use of AI tools.
• Education & cognitive development. We have already seen negative impacts of social media technology on cognitive development. AI poses an even larger risk. It is still unknown how outsourcing of fundamentals like math, logic and prose to AI may stunt cognitive development. On the other hand, use of AI tools can in potentially stimulate creativity and accelerate learning and providing students access to AI tools will improve their facility with these tools and thus opportunities for employment.
• Data security. AI feeds on data – we should therefore see Canadian data as one of our most valuable natural resources. Data insecurity means not only infringements of privacy but loss of valuable intellectual property.
• Political risk. We have already seen impact of AI on politics through social media chatbots and deepfakes. These impacts will increase with improvements to generative AI for language, voice, images and video.

Beyond regulation there are some things the Government of Canada can do to mitigate these risks. We need to support research on labour market shifts and then act on this research to invest in retraining. We also need to invest in education research on how AI can be most effectively integrated into our education systems, with a particular focus on the development of fundamental human intellectual capacities, including logic, memory, analysis, communication and creativity.

REGULATION:

There is concern regarding the potential for agentic AI to run amok. I do not think there needs to be regulation specific to AI to mitigate this risk. Rather, I think we should rely upon our existing system of laws, introducing new ones where specifically needed. For example, a motor vehicle should be safe whether or not it is driven by a human or an AI. Our children should be protected from addictive social media patterns whether they include real or AI content.

Mitigating political risk may entail stronger legislation requiring clear watermarking of AI content and significant penalties for infractions.

We need to protect valuable personal data of Canadians, particularly from foreign actors, and protecting creative content from plagiarism and copyright infringement. The Government of Canada can mitigate risks through data sovereignty programs and assistance to individuals and organizations in enforcement of copyright law.

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The CINTHeA project is a collaboration between Connected Minds researchers at , and . Working with industry and public sector partners, the CINTHEA project seeks to understand and address the challenges faced by older adults in maintaining their physical, cognitive, and social health. Neuroscience research will identify salient biomarkers for physical/cognitive/social health. In parallel, AI/robot research will focus on automatic detection of these neuro-markers while interacting with, assisting and engaging older adults in their communities.

Application Process

We welcome applicants with doctoral training in related fields, including cognitive neuroscience, kinesiology, rehabilitation sciences, robotics, computer vision and AI. Successful applicants will be supervised by CINTHeA faculty researchers and conduct research as part of an interdisciplinary team.

Please send a cover letter and cv to no later than Sept 19, 2025. In your cover letter, please summarize relevant experience and indicate names of potential supervisors from the list below. Short-listed candidates will be invited to apply for a two- year Connected Minds Postdoctoral Fellowship to support their participation in the CINTHeA project (deadline Sept 29, 2025).

CINTHeA Investigators & Collaborators

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York is exploring potential collaborations with Goethe University in Frankfurt, Germany.

For CAIS, a possible partner is the

This is a relatively new centre that is hiring many new faculty this year.  I have listed some of these faculty below with their research interests and links to their Google Scholar pages. There is support available to sponsor short visits of our faculty to Goethe University and to reciprocally invite them to visit us. If you are potentially interested in participating in this exchange can you please send an email to caisinfo@yorku.ca

surveillance, authoritarianism, data justice, ICT4D, smart cities

climate change, sustainable development

Algorithm Engineering, Graph Algorithms, Parallelism, Memory Hierarchies

climate tipping elements, Earth system stability, Anthropocene, complex systems, nonlinear dynamics

Biodiversity, Ecology&Evolution, Computational Biology, Biogeography, Complex Systems Modelling

Many Thanks,

James H. Elder
Professor & York Research Chair in Human and Computer Vision
Co-Director, Centre for AI & Society
Department of Electrical Engineering & Computer Science, Lassonde School of Engineering
Department of Psychology, Faculty of Health

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Shayna Rosenbaum is a Professor and York Research Chair in the Clinical Neuropsychology Stream, Adult Clinical Area, Department of Psychology, Centre for Integrative and Applied Neuroscience, and the CFREF-funded Vision: Science to Applications (VISTA) and Connected Minds: Neural and Machine Systems for a Healthy, Just Society programs. She is an Adjunct Scientist at the Rotman Research Institute at Baycrest and registered as a Clinical Neuropsychologist with the College of Psychologists and Behaviour Analysts of Ontario. She received her Ph.D. in Psychology from the University of Toronto in 2004 and completed a postdoctoral fellowship at the Rotman. She has published extensively on the topics of memory and decision-making, and has received awards for her neuroimaging and patient research, including a Sloan Research Fellowship and early career awards from the Canadian Association for Neuroscience, Canadian Society for Brain Behaviour and Cognitive Science (CSBBCS), and International Neuropsychological Society. Her research is funded by the Canadian Institutes of Health Research and the Natural Sciences and Engineering Research Council of Canada. She is an elected member (emerita) of the Royal Society of Canada College of New Scholars, Artists, and Scientists and past member of the Board of Trustees of the Ontario Science Centre. (from: )

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