UQAM

A successful inaugural Global Dialogue on AI Governance should achieve tangible progress in establishing common principles, fostering collaboration, and identifying actionable pathways for responsible AI development. First, it should produce a clear, shared understanding of the risks and opportunities of AI across social, economic, cultural, and technical dimensions, ensuring all stakeholders—governments, civil society, academia, and the private sector—align on foundational priorities. Second, the dialogue should identify mechanisms for international cooperation on safety, security, and ethical standards. Establishing frameworks for transparency, accountability, human oversight, and data governance would create a foundation for consistent AI practices globally. Third, it should emphasize capacity-building and knowledge-sharing, especially for developing countries and underrepresented communities. Supporting equitable access to AI tools, expertise, and education will ensure that governance approaches are inclusive and globally relevant. Fourth, the dialogue should highlight cross-cutting challenges, such as environmental impacts, bias and fairness, and emerging technological risks. Raising awareness and initiating multilateral strategies for these issues can accelerate preemptive policy development. Finally, success would be reflected in concrete next steps, including commitments to ongoing collaboration, pilot projects, open data initiatives, and multi-stakeholder partnerships. The first dialogue should serve not only as a forum for discussion but as a launchpad for coordinated, actionable efforts that translate principles into measurable outcomes. In essence, success is defined by the creation of a global, inclusive, and actionable framework for AI governance that balances innovation with safety, fairness, and respect for human rights.

• Safe, secure and trustworthy AI
• AI capacity-building
• Protection and promotion of human rights
• Transparency, accountability, and human oversight

These priorities reflect the most urgent and impactful dimensions of AI governance. Safe, secure, and trustworthy AI is fundamental to preventing misuse and ensuring AI systems do not harm society or exacerbate inequalities. Establishing robust safety standards and security protocols will build public trust and enable responsible innovation. AI capacity-building is critical, particularly for developing nations and smaller organizations, to ensure equitable access to AI tools and expertise. Strengthening capacity promotes inclusion and empowers stakeholders to participate meaningfully in AI governance discussions. Protection and promotion of human rights ensures that AI deployment aligns with global legal and ethical frameworks, guarding against biases, discrimination, and infringements on privacy. Human-centric AI must prioritize fairness, dignity, and non-discrimination. Transparency, accountability, and human oversight are essential for trust and governance. Clear documentation, auditability, and mechanisms for human intervention can prevent opaque decision-making and hold developers and deployers accountable for AI outcomes. Together, these priorities create a balanced approach that encourages innovation while mitigating risks, promoting equity, and respecting fundamental rights. They ensure that AI governance is not only reactive but proactive, anticipatory, and inclusive.

While the listed themes are comprehensive, several cross-cutting issues merit additional attention. Environmental sustainability is increasingly relevant, as large-scale AI models consume significant energy and natural resources. Integrating eco-conscious AI practices can align technological development with global climate goals. AI and geopolitical dynamics is another emerging concern. AI capabilities influence global security, trade, and international power structures. Addressing these risks through multilateral dialogue is essential to avoid conflict and ensure cooperative frameworks. Addressing these cross-cutting issues will strengthen the dialogue's relevance, ensuring that AI governance is forward-looking, holistic, and adaptable to emerging global challenges.

In the Montreal region, the rapid expansion of AI-powered data centers highlights significant governance gaps in environmental sustainability, energy management, and responsible AI deployment. These facilities consume enormous amounts of electricity, often generated from fossil fuels, contributing to deforestation and local ecological degradation, including the loss of surrounding trees. This reflects broader challenges in ensuring AI development aligns with environmental and social responsibility. Key challenges include the absence of robust regulations for sustainable energy use in AI infrastructure and limited oversight of environmental impacts. The lack of standardized frameworks for monitoring and reporting energy consumption means negative ecological consequences can occur unchecked. Additionally, the concentration of AI infrastructure in sensitive regions raises public concern and reputational risks for both private companies and policymakers. At the same time, these challenges present opportunities. Developing policies that mandate green energy adoption, carbon offsets, and sustainable land use for data centers could position the region as a leader in environmentally responsible AI. There is also potential to advance transparent reporting, human oversight, and accountability in AI operations, creating models for balancing technological growth with ecological protection.

The AI Dialogue can serve as a critical platform for global coordination, enabling countries, international organizations, private sector actors, and civil society to converge around shared principles for responsible AI. By facilitating dialogue, knowledge exchange, and consensus-building, it can help establish common standards for safe, secure, and trustworthy AI while addressing ethical, social, and human rights considerations. The Dialogue can also bridge gaps between developed and developing nations by highlighting capacity-building needs, promoting equitable access to AI technologies, and enabling participation in policy and regulatory design. This inclusive approach strengthens global trust and ensures that AI benefits are broadly shared. Furthermore, the Dialogue can act as a hub for multi-stakeholder collaboration, connecting regulatory frameworks, research efforts, and technical innovations across borders. It can catalyze joint initiatives on transparency, accountability, interoperability, and human oversight, ensuring that AI governance evolves consistently and coherently worldwide. Ultimately, the AI Dialogue can transform international cooperation from ad hoc discussions into structured, actionable collaboration, providing a roadmap for sustainable, ethical, and human-centered AI development globally.

In Canada, initiatives such as OBVIA (Observatoire international sur les impacts sociétaux de l'IA), a network of over 300 researchers in Quebec, and the leadership of Prof. Yoshua Bengio at Université de Montréal—representing Canada at the UN—demonstrate strong foundations in AI research, ethics, and policy engagement. These entities have advanced knowledge on the social, ethical, and human rights dimensions of AI, contributing to evidence-based policy recommendations and international discourse. However, there remain gaps in translating this expertise into coordinated global governance frameworks. Existing initiatives often operate within national or regional boundaries, and insights from academia, civil society, and research networks are not yet fully integrated into multilateral AI policymaking. The AI Dialogue can build on these strengths by connecting regional expertise with international efforts, such as UNESCO's Recommendation on the Ethics of AI, the OECD AI Principles, and the Global Partnership on AI (GPAI). By providing a structured forum for sharing research, best practices, and lessons learned, it can harmonize approaches, promote interoperability, and accelerate adoption of responsible AI governance globally. The Dialogue's added value lies in its ability to bridge knowledge, policy, and practice across borders. It can facilitate collaboration among researchers, governments, and multilateral institutions; identify priority areas for action; and promote multi-stakeholder engagement. By leveraging Canada's expertise while addressing remaining gaps, the AI Dialogue can help translate cutting-edge research and ethical guidance into actionable, globally-relevant AI governance frameworks.

Different stakeholders—governments, academia, civil society, the private sector, and international organizations—can contribute by sharing expertise, research, and practical experiences in AI deployment, governance, and ethics. Governments can provide policy perspectives and regulatory needs; researchers can offer evidence-based analysis and risk assessments; civil society can highlight societal and human rights implications; and the private sector can share insights on technological feasibility and innovation challenges. To maximize impact, the Dialogue's format should be multi-stakeholder, inclusive, and action-oriented. It could combine plenary sessions to establish shared principles, thematic working groups to address specific challenges, and interactive workshops to co-develop solutions. Regular reporting mechanisms, open documentation, and digital participation platforms can ensure transparency and broad engagement. Structured follow-ups, such as commitments to pilot projects, shared research repositories, and regional consultation mechanisms, would allow dialogue outcomes to translate into concrete actions, reinforcing collaboration and accountability.

Global AI governance discussions often emphasize governments, major tech companies, and established academic institutions, leaving non-traditional paths and atypical students—like early-career researchers, self-taught technologists, and learners outside formal education systems—underrepresented. These voices bring fresh perspectives, innovative problem-solving approaches, and lived experiences that can challenge conventional assumptions about AI ethics, fairness, and societal impact. Inclusion can be achieved through dedicated participation pathways for atypical learners, such as scholarships, mentorship programs, and outreach initiatives that invite contributions from diverse educational and professional backgrounds. Online platforms, open calls for research proposals, and community-driven workshops can amplify their voices. Structured peer networks and collaboration with universities or research centers can also provide support for non-traditional participants to meaningfully engage in technical and policy discussions. By integrating these perspectives, the AI Dialogue can foster more inclusive and creative solutions to AI governance challenges. Non-traditional participants can highlight overlooked social impacts, propose novel approaches to transparency and accountability, and contribute to bridging gaps between formal institutions and grassroots communities. Their engagement ensures that AI policies are not only technically sound but socially relevant and accessible, promoting equity and broader trust in AI systems. In short, actively welcoming non-traditional students and atypical contributors strengthens the dialogue, diversifies problem-solving approaches, and enriches global AI governance with perspectives that might otherwise remain unheard.

Meaningful engagement can be fostered through hybrid and interactive formats that combine in-person and virtual participation. Breakout workshops and thematic labs allow focused problem-solving on topics like AI safety, ethics, and human rights. Multi-stakeholder hackathons, simulations, or scenario exercises can generate practical solutions while encouraging collaboration across sectors. Digital platforms enabling asynchronous discussions, polling, and open data sharing ensure broader participation, particularly from underrepresented regions. "Town-hall" style dialogues and Q&A sessions with experts promote transparency and active engagement. Gamified formats, challenge-based learning, and collaborative research showcases can encourage youth, academia, and private-sector innovators to contribute creatively. Finally, structured feedback loops and public reporting ensure that dialogue outputs are actionable and reflect diverse voices, bridging the gap between discussion and global policy implementation.

Several policies, practices, and platforms around the world provide concrete solutions for responsible AI development and governance. The OECD AI Principles offer internationally recognized guidelines emphasizing human-centric AI, transparency, accountability, and fairness. Countries such as Canada and the EU have translated these principles into national AI strategies, integrating regulatory frameworks, ethical guidelines, and monitoring mechanisms to guide AI deployment responsibly. UNESCO's Recommendation on the Ethics of AI provides another benchmark, promoting inclusivity, human rights protection, and sustainable AI use. These frameworks guide governments, organizations, and researchers in evaluating AI impacts on society and mitigating risks. At the organizational level, platforms such as the Global Partnership on AI (GPAI) foster multi-stakeholder collaboration, enabling shared research, best practices, and capacity-building initiatives. Similarly, research networks like OBVIA in Quebec bring together over 300 researchers to study the societal and ethical impacts of AI, translating academic insights into policy recommendations. Practical approaches include algorithmic audits, transparent reporting of AI systems, and human-in-the-loop oversight, which help detect bias, ensure accountability, and maintain public trust. Open-source AI frameworks and responsible data practices also promote interoperability, transparency, and equitable access to AI tools. Collectively, these policies, platforms, and practices demonstrate that effective AI governance is achievable when ethical principles, technical safeguards, multi-stakeholder engagement, and evidence-based policymaking converge. They provide models that can be adapted and scaled internationally, addressing challenges while promoting innovation and societal benefit.