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Teaching AI for public policy

Artificial intelligence is quickly becoming part of how policy professionals research and communicate, and the Max Bell School of Public Policy wants to make sure its community is ready. This spring, the school launched an internal AI policy workshop series to help staff and students build practical skills and to think critically about how these tools fit into the work of policy practitioners. 

The series was organized by Neil Bouwer, Professor of Practice at Max Bell, and Anna Jahn and Aengus Bridgman from the Centre for Media, Technology, and Democracy. Together, they brought Max Bell personnel across the roles into the same room for open, hands-on conversations about what AI can and can’t do, and what it means for the future of policy work. The workshops build on one another, starting with the fundamentals of artificial intelligence and progressing to applied and skill-building sessions. 

During the introductory workshop, Bridgman encouraged the room to set aside bigger debates about job displacement and automation for the day, and instead asked a simple question: how can we get these tools to actually work for us? 

From there, he walked participants through the difference between chatbots and AI agents. A chatbot, he explained, is like a browser tab where you copy, paste, and go back and forth. The agent is quite different. It operates within your system and can access your files to carry out tasks on your behalf. To show what that looks like in practice, Bridgman demonstrated how a command-line tool paired with a large language model could pull and analyze unemployment data from Statistics Canada in under a minute—something that would normally take an analyst with technical expertise much longer. 

“We are moving very quickly from a world where decisions and thinking about things were sort of the start of a project, and then the building and implementing was the very costly part,” Bridgman explained. “This is being reversed. The really costly part of that process is no longer the implementation. It’s the meeting. It's the conversation. It’s the visioning.” 

One idea that came from the session was thinking about AI agents like interns: they’re clear in their direction and have good reference materials to work with. Bridgman stressed that responsibility for the final product always sits with the user, noting that “the intern is never responsible for the work. You are responsible. The manager always has their name on it.” 

That message resonated with MPP student Adam McKay. He said the workshops changed how he thinks about AI in the workplace. “I think what I’ve mainly started to think differently about is the notion that AI is going to replace everybody’s jobs,” he reflected. “What’s more likely is that there’s going to be a shift by employers to prioritizing hiring employees that understand how to use AI and know how to leverage its efficiency.” 

McKay further highlighted the potential for mid-level and senior employees to use agents that might typically fall to junior staff, freeing up more time and energy for the problem-solving side of policy work. 

Participants also raised important questions about data privacy, how to verify AI-generated content, and the risk of hallucinations, where AI produces information that sounds right but isn’t. Bridgman was upfront about the limitations but noted that providing strong context and documentation significantly reduces these risks. He also encouraged participants to use the tools themselves as a check, noting that one agent can be used to fact-check another's output. 

The introductory workshop wrapped up with hands-on exercise. Participants used Gemini, Google’s AI model, to tackle real tasks from their own work, whether that meant drafting a policy brief, exploring a dataset, or testing how the tools handle specialized queries.  

MacKay describes the series as “a fantastic entry into being able to understand AI at a little bit of a deeper level, and to really start to get you on the path to gaining the skills to be able to leverage it in your career.” 

With more sessions to come, the Max Bell School’s AI policy workshop series continues to build knowledge and confidence across the team. It’s one more example of how the school is preparing its community not just to understand the policy challenges of today, but to work with the tools that are shaping how those challenges will be addressed. 

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