Perceptions of Canada’s AI Governance System: Findings from Interviews with 20 Government Leaders & Subject Matter Experts

Abstract

This report presents data and findings from a macro-scale study of Canada’s national AI governance system. Drawing on interviews with government leaders and subject matter experts that were conducted throughout 2023, we discuss the actors, impacts, resources, networks, activities, logics, norms, and rules involved in structuring and operating the national AI governance system of Canada. We provide new empirical data on AI governance practices, new theoretical models of AI governance across micro and macro scales, in-depth analysis of Canada's AI governance system, and implications for future AI governance research, practice, and policy.

Based on findings from our interviews, we suggest three directions for future research: (1) conduct additional analysis of the 610 topics in our dataset, (2) further investigate institutional and ecosystem-level structures and dynamics in Canada’s national AI governance system, (3) apply our framework, data, and findings to study other AI governance systems. We also suggest four strategic objectives for strengthening Canada's AI governance system, along with several interventions that can be enacted in support of each of the four strategic objectives: (1) implement new collaboration and coordination mechanisms, (2) create guidance for designing and implementing participatory AI governance initiatives, (3) expand access to key resources needed for effective AI governance practices, (4) advance diversity, equity, and inclusion in AI governance activities.

Keywords: Artificial intelligence, governance, policy, strategy, service systems, thematic analysis, expert interviews, elicitation