UBC is part of a national effort led by the Canadian Institute for Advanced Research (CIFAR) to address urgent challenges in artificial intelligence (AI) safety.
As AI technologies become increasingly embedded in professional, economic and democratic processes, there is a growing need for approaches that integrate ethical, social and governance considerations. These research projects will address the most urgent challenges in the safety, accountability, and ethical deployment of AI.
Through the Canadian AI Safety Institute (CAISI) Research Program at CIFAR interdisciplinary projects across Canada are bringing together expertise from computer science, economics, sociology and Indigenous governance. Their work aims to strengthen accountability frameworks, support ethical deployment and ensure that AI systems align with public interest and human well-being.
UBC-led and co-led projects
Addressing AI-safety through Indigenous community-based governance
Victoria Lemieux (University of British Columbia), Jacob Taylor (First Nations University), Robin Billy (Secwepemc Nation), Ethan Clark (Nationsfirst Technologies)
This project addresses the critical gap in current AI safety frameworks, which often overlook Indigenous rights and data sovereignty. By treating AI safety as a “common-pool resource,” the project team combines Elinor Ostrom’s commons theory with the Haudenosaunee Great Law of Peace to co-create a community-led governance model. Using decentralized infrastructure and privacy-enhancing technologies, the initiative will test this framework in a “living lab” setting. Ultimately, the project supports economic reconciliation by empowering Indigenous communities to oversee AI implementation, ensuring technology respects cultural heritage and seven-generation stewardship.
Economic foundations of AI certification
Jesse Perla (University of British Columbia), Kevin Leyton-Brown (Canada CIFAR AI Chair, Amii, University of British Columbia), Serena Wang (University of British Columbia)
This project addresses the urgent need for robust AI oversight as models demonstrate increasingly superhuman yet unpredictable capabilities. While current regulations focus on technical malfunctions, they lack a framework for certifying AI in specific professional roles. By integrating economic theory and computer science, the project team will develop a “safety-through-certification” framework that evaluates economic rationality and models multiagent interactions using behavioral game theory. Ultimately, the project provides a blueprint for domain-specific certification standards, ensuring agentic AI remains accountable and aligned with human welfare across sectors like healthcare and finance.
The AI Safety Catalyst Projects are funded by the Department of Innovation, Science and Economic Development Canada (ISED) through the federally-led Canadian AI Safety Institute.
CIFAR announcement and full list of awarded projects