AI Governance on the Ground: Canada's Algorithmic Impact Assessment Process and Algorithm Has Evolved

Summary

This report offers a rare behind-the-scenes look at how Canada's pioneering Algorithmic Impact Assessment (AIA) framework actually works in practice. Through candid interviews with Treasury Board oversight team members and a Canadian immigration lawyer, it reveals the gap between policy intentions and real-world implementation. The report goes beyond theoretical frameworks to examine actual cases, particularly in immigration, showing how the AIA process has evolved since its 2019 launch and where it's succeeding—or falling short—in its goal of making government AI more accountable.

What makes this different

Unlike most AI governance resources that focus on policy design or theoretical frameworks, this report examines the messy reality of implementation. It provides insider perspectives from the people actually running Canada's AIA process and practitioners dealing with its outcomes. The immigration case studies are particularly valuable, showing how algorithmic decision-making affects real people's lives and how legal professionals are adapting to challenge automated government decisions. This ground-level view makes it essential reading for anyone wondering whether impact assessments actually work in practice.

Key insights from the field

• The human factor remains critical: Despite automation, human oversight continues to play a crucial role in the AIA process, though not always in the ways originally envisioned.
• Implementation varies across departments: Different government departments have interpreted and applied the AIA requirements differently, creating inconsistencies in how algorithmic systems are assessed and monitored.
• Legal challenges are emerging: Immigration lawyers are developing new strategies to challenge algorithmic decisions, creating precedents that could influence future AI governance approaches.
• The assessment process is iterative: Canada's AIA framework has undergone significant changes based on real-world feedback, demonstrating the importance of adaptive governance approaches.
• Documentation gaps persist: While the AIA requires extensive documentation, gaps remain in how algorithmic systems are explained to affected individuals and their representatives.

Who this resource is for

• Policy implementers in government agencies tasked with operationalizing AI governance frameworks
• Legal practitioners dealing with algorithmic decision-making, particularly in immigration and administrative law
• AI governance researchers studying the practical effectiveness of impact assessment tools
• International policymakers considering similar frameworks and wanting to learn from Canada's experience
• Civil society advocates seeking to understand how to engage with and challenge government AI systems
• Government officials in other jurisdictions evaluating whether to adopt Canada's AIA model

Real-world applications

Use this report to understand how theoretical AI governance translates into practice. It's particularly valuable for identifying potential implementation challenges before they occur, developing training programs for government staff, and creating realistic expectations about what impact assessments can and cannot achieve. Legal professionals will find the immigration case studies especially useful for understanding how to navigate algorithmic decision-making in their practice.

Watch out for

This report reflects the Canadian context and legal system, which may not directly translate to other jurisdictions. The findings are based on a limited number of interviews and may not represent the full scope of AIA implementation across all Canadian government departments. Additionally, the report captures the AIA process at a specific point in time—ongoing evolution means some insights may become outdated as the framework continues to develop.