From Public Office to AI Governance

Three years ago, I watched a young candidate stand on a street corner in Vancouver, clipboard in hand, asking passersby to care about climate change. He lost that race. Then he lost another. And another. Most people would have walked away, convinced the system didn't want them. But Wyatt Tessari L'Allié did something unexpected: he stopped trying to fix the present and started building guardrails for the future. Today, he's not campaigning for votes—he's campaigning for something far harder to secure: public trust in artificial intelligence.

When I sat down with Wyatt for this episode, I expected to hear the familiar arc of disillusionment that pushes activists out of politics. Instead, I found someone who had discovered a more urgent arena. His journey from mechanical engineering student to three-time political candidate to founder of AIGS Canada isn't a story of career pivots—it's a masterclass in recognizing where your skills matter most. And right now, he believes that place is AI governance.

The conventional wisdom says you need deep technical expertise to shape AI policy. Wyatt proves otherwise. His background in climate activism taught him something technologists often miss: the hardest part of managing transformative technology isn't the engineering—it's getting people to care before the crisis hits. Climate change offered a decades-long warning period that we largely squandered. Artificial intelligence is moving faster. The window between "this seems important" and "this is reshaping everything" has collapsed from generations to years, perhaps months. Wyatt's insight, born from standing on those street corners and knocking on thousands of doors, is that we can't afford the same delay with AI. The public conversation needs to happen now, while there's still time to influence the trajectory.

That's why he founded AIGS Canada—a network dedicated to AI safety and responsible governance. What strikes me about his approach is its democratic foundation. He's not interested in letting a handful of Silicon Valley executives or government officials decide our AI future behind closed doors. Instead, he's building coalitions that bring diverse voices into the room: ethicists, policy makers, community organizers, people who understand that technology doesn't land neutrally in society. It amplifies existing power structures unless we intentionally design it otherwise. His filmmaking background shows up here too—he knows how to tell stories that make abstract risks feel personal, that translate "existential threat" into something a municipal councilor or small business owner can grasp and act upon.

During our conversation, Wyatt emphasized something I've been thinking about constantly: the gap between AI's capabilities and our collective readiness to govern it. We're deploying systems that can generate convincing misinformation, automate away entire job categories, and make life-altering decisions about credit, healthcare, and criminal justice—often with less regulatory oversight than we apply to new toasters. This isn't hyperbole. It's the uncomfortable reality that keeps him working sixteen-hour days. His mechanical engineering training gives him enough technical literacy to understand what's under the hood, but his real value is translation. He can sit with researchers worried about alignment problems and then walk into a legislative office and explain why that matters for their constituents' jobs, privacy, and democratic institutions.

The political losses that might have broken someone else instead refined Wyatt's understanding of how change actually happens. Running for office taught him that you don't need to win elections to shift policy—you need to make certain ideas politically unavoidable. Climate activists spent decades doing this work, and though progress remains frustratingly slow, the conversation has fundamentally changed. No serious politician today denies that climate is an issue requiring response, even if they disagree on solutions. Wyatt is applying that same long-game strategy to AI governance. AIGS Canada isn't trying to stop AI development—that's neither possible nor desirable. Instead, it's working to ensure that as these systems grow more powerful, we have frameworks in place that prioritize human agency, fairness, and accountability.

What I find most compelling about Wyatt's approach is his refusal to get trapped in either techno-utopianism or techno-pessimism. He's clear-eyed about both AI's extraordinary potential and its genuine risks. This balanced perspective is rare and desperately needed. Too many conversations about AI devolve into either breathless hype about solving every human problem or apocalyptic warnings about killer robots. The actual governance challenge sits in the messy middle: How do we encourage beneficial innovation while preventing exploitation? How do we make AI systems transparent enough to audit without revealing proprietary information that enables misuse? How do we ensure that the people most affected by algorithmic decisions have a say in how those systems are designed? These aren't questions with obvious answers, but they're the ones Wyatt wakes up trying to solve.

His path offers a blueprint for others feeling overwhelmed by AI's trajectory. You don't need a PhD in machine learning to contribute meaningfully to AI governance. You need the courage to engage, the humility to keep learning, and the strategic sense to know where your particular skills—whether legal, creative, organizational, or interpersonal—can make a difference. Wyatt brought his activist instincts, his communication skills, and his stubborn refusal to accept that important conversations should happen only among technical elites. That combination is proving more valuable than another computer science degree.

As we closed our conversation, I kept thinking about those three lost elections and how differently Wyatt's story could have unfolded if he'd won. He might be focused on municipal zoning bylaws or provincial healthcare budgets—important work, but arguably narrow in scope. Instead, those losses freed him to pursue something larger: helping shape how humanity navigates its most consequential technological transition since the industrial revolution. Sometimes failure isn't a dead end—it's a redirection toward the work only you can do.

The future of AI won't be determined solely in research labs or boardrooms. It will be shaped by people like Wyatt who insist that these decisions belong to all of us—and who build the structures to make democratic participation possible.# From Public Office to AI Governance

Three years ago, I watched a young candidate stand on a street corner in Vancouver, clipboard in hand, asking passersby to care about climate change. He lost that race. Then he lost another. And another. Most people would have walked away, convinced the system didn't want them. But Wyatt Tessari L'Allié did something unexpected: he stopped trying to fix the present and started building guardrails for the future. Today, he's not campaigning for votes—he's campaigning for something far harder to secure: public trust in artificial intelligence.

When I sat down with Wyatt for this episode, I expected to hear the familiar arc of disillusionment that pushes activists out of politics. Instead, I found someone who had discovered a more urgent arena. His journey from mechanical engineering student to three-time political candidate to founder of AIGS Canada isn't a story of career pivots—it's a masterclass in recognizing where your skills matter most. And right now, he believes that place is AI governance.

The conventional wisdom says you need deep technical expertise to shape AI policy. Wyatt proves otherwise. His background in climate activism taught him something technologists often miss: the hardest part of managing transformative technology isn't the engineering—it's getting people to care before the crisis hits. Climate change offered a decades-long warning period that we largely squandered. Artificial intelligence is moving faster. The window between "this seems important" and "this is reshaping everything" has collapsed from generations to years, perhaps months. Wyatt's insight, born from standing on those street corners and knocking on thousands of doors, is that we can't afford the same delay with AI. The public conversation needs to happen now, while there's still time to influence the trajectory.

That's why he founded AIGS Canada—a network dedicated to AI safety and responsible governance. What strikes me about his approach is its democratic foundation. He's not interested in letting a handful of Silicon Valley executives or government officials decide our AI future behind closed doors. Instead, he's building coalitions that bring diverse voices into the room: ethicists, policy makers, community organizers, people who understand that technology doesn't land neutrally in society. It amplifies existing power structures unless we intentionally design it otherwise. His filmmaking background shows up here too—he knows how to tell stories that make abstract risks feel personal, that translate "existential threat" into something a municipal councilor or small business owner can grasp and act upon.

During our conversation, Wyatt emphasized something I've been thinking about constantly: the gap between AI's capabilities and our collective readiness to govern it. We're deploying systems that can generate convincing misinformation, automate away entire job categories, and make life-altering decisions about credit, healthcare, and criminal justice—often with less regulatory oversight than we apply to new toasters. This isn't hyperbole. It's the uncomfortable reality that keeps him working sixteen-hour days. His mechanical engineering training gives him enough technical literacy to understand what's under the hood, but his real value is translation. He can sit with researchers worried about alignment problems and then walk into a legislative office and explain why that matters for their constituents' jobs, privacy, and democratic institutions.

The political losses that might have broken someone else instead refined Wyatt's understanding of how change actually happens. Running for office taught him that you don't need to win elections to shift policy—you need to make certain ideas politically unavoidable. Climate activists spent decades doing this work, and though progress remains frustratingly slow, the conversation has fundamentally changed. No serious politician today denies that climate is an issue requiring response, even if they disagree on solutions. Wyatt is applying that same long-game strategy to AI governance. AIGS Canada isn't trying to stop AI development—that's neither possible nor desirable. Instead, it's working to ensure that as these systems grow more powerful, we have frameworks in place that prioritize human agency, fairness, and accountability.

What I find most compelling about Wyatt's approach is his refusal to get trapped in either techno-utopianism or techno-pessimism. He's clear-eyed about both AI's extraordinary potential and its genuine risks. This balanced perspective is rare and desperately needed. Too many conversations about AI devolve into either breathless hype about solving every human problem or apocalyptic warnings about killer robots. The actual governance challenge sits in the messy middle: How do we encourage beneficial innovation while preventing exploitation? How do we make AI systems transparent enough to audit without revealing proprietary information that enables misuse? How do we ensure that the people most affected by algorithmic decisions have a say in how those systems are designed? These aren't questions with obvious answers, but they're the ones Wyatt wakes up trying to solve.

His path offers a blueprint for others feeling overwhelmed by AI's trajectory. You don't need a PhD in machine learning to contribute meaningfully to AI governance. You need the courage to engage, the humility to keep learning, and the strategic sense to know where your particular skills—whether legal, creative, organizational, or interpersonal—can make a difference. Wyatt brought his activist instincts, his communication skills, and his stubborn refusal to accept that important conversations should happen only among technical elites. That combination is proving more valuable than another computer science degree.

As we closed our conversation, I kept thinking about those three lost elections and how differently Wyatt's story could have unfolded if he'd won. He might be focused on municipal zoning bylaws or provincial healthcare budgets—important work, but arguably narrow in scope. Instead, those losses freed him to pursue something larger: helping shape how humanity navigates its most consequential technological transition since the industrial revolution. Sometimes failure isn't a dead end—it's a redirection toward the work only you can do.

The future of AI won't be determined solely in research labs or boardrooms. It will be shaped by people like Wyatt who insist that these decisions belong to all of us—and who build the structures to make democratic participation possible.