Canada's federal government is using artificial intelligence to analyze more than 11,000 public comments submitted during consultation on updates to its national AI strategy, Artificial Intelligence Minister Evan Solomon confirmed Thursday. The government developed an internal AI platform to translate and summarize the extensive public feedback, with Solomon stating the work complies with Treasury Board rules and that all comments will be made public once the analysis is complete. The approach represents a practical application of AI for business in government operations, while also raising questions about using AI systems to shape the very policies that will govern artificial intelligence development and deployment.
The irony of employing AI to determine AI policy has not been lost on observers, who note this creates potential circular dependencies where algorithmic analysis influences the regulatory frameworks that will govern those same algorithms.
AI Analyzing AI Policy Feedback
The Canadian government's public consultation on its national AI strategy update generated over 11,000 submissions from citizens, industry stakeholders, researchers, and advocacy groups. Manually reviewing, translating, and synthesizing this volume of feedback would require months of staff time and substantial costs.
The internally developed AI platform automates several key functions including translating submissions between English and French, Canada's official languages, identifying common themes and concerns across thousands of comments, summarizing key arguments and recommendations, and categorizing feedback by topic area and stakeholder type.
This application represents precisely the kind of AI automation that governments worldwide are exploring to improve efficiency and responsiveness. However, it also introduces questions about algorithmic bias, accuracy, and transparency when AI systems influence policy development.
Treasury Board Compliance and Oversight
Minister Solomon emphasized the AI analysis complies with Treasury Board rules, suggesting the government followed established protocols for AI deployment in federal operations. Canada's Treasury Board has been developing governance frameworks for AI use across government departments, including requirements for transparency, accountability, and human oversight.
These frameworks likely require human review of AI-generated summaries, documentation of the AI system's capabilities and limitations, mechanisms to identify and correct errors or biases, and transparency about how AI analysis influenced final policy decisions.
The commitment to publishing all comments once analysis is complete provides a check on the AI system's work—citizens and organizations can verify their submissions were accurately represented and that the AI didn't systematically misinterpret or exclude certain perspectives.
Efficiency Gains Versus Accountability Questions
Using AI tools for analyzing public consultations delivers clear efficiency advantages. Government staff can process vastly more feedback in less time, potentially making public consultation more meaningful by actually incorporating diverse input rather than selectively sampling due to resource constraints.
The AI system can also identify patterns across thousands of submissions that human analysts might miss, surfacing minority viewpoints or emerging concerns that could be lost in manual review processes.
However, accountability challenges emerge when AI mediates between citizens and policymakers. If the AI system systematically underweights certain arguments, misinterprets technical submissions, or fails to capture nuance in complex policy positions, those biases could materially affect policy outcomes.
The concern intensifies because this particular consultation addresses AI policy itself. If the AI analysis tool reflects assumptions or limitations that shape which public concerns receive prominence, it could influence the very regulations designed to address those limitations.
International Context for AI in Governance
Canada joins a growing list of governments deploying artificial intelligence for administrative and policy functions. The European Union uses AI to analyze public consultations on various policy matters. Singapore's government employs AI for citizen service delivery and policy research. The United States federal agencies increasingly use AI for processing applications, analyzing data, and supporting decision-making.
However, most governments have been cautious about AI's role in policy development itself, maintaining that humans must make final decisions about regulatory frameworks and legislative priorities. Canada's approach—using AI to summarize but not decide policy—attempts to balance efficiency gains with democratic accountability.
Transparency and Public Trust
The government's commitment to publishing all 11,000 comments creates transparency that addresses some accountability concerns. Citizens, journalists, and researchers can examine the raw data and evaluate whether the AI-generated summaries accurately reflect public input.
This transparency distinguishes Canada's approach from black-box AI systems where neither inputs nor analytical processes are visible to outside scrutiny. However, questions remain about whether the government will also publish details about the AI system itself—its architecture, training data, validation testing, and known limitations.
Minister Solomon's portfolio as Canada's first dedicated AI Minister puts him in a unique position to demonstrate responsible AI governance. How the government handles this consultation analysis could set precedent for AI use across Canadian federal operations and influence other democracies considering similar approaches.
Implications for Democratic Process
The use of AI in policy development raises fundamental questions about democratic legitimacy and representation. When algorithms mediate between citizens and their government, does the relationship change in ways that matter for accountability and trust?
Proponents argue AI enables more participatory democracy by making it feasible to genuinely consider thousands of citizen submissions rather than relying on small focus groups or surveys. Critics worry that algorithmic summaries, however well-designed, inevitably impose structure and emphasis that reflects the system designers' assumptions rather than pure citizen voice.
The Canadian government's approach of using AI for analysis while maintaining human decision-making and full transparency represents an attempt to capture efficiency benefits while preserving democratic accountability. Whether this balance succeeds could influence how democracies worldwide approach AI in governance.
