| Issue/Objective |
The rapid integration of generative artificial intelligence (GenAI) into mental health support is often framed as a solution to downstream access barriers such as cost, stigma, and provider shortages. However, this framing risks obscuring upstream determinants of health equity, including governance structures, power asymmetries, financial stewardship, and policy accountability. This study examines how Canadian and international policy discourse constructs AI as a digital therapeutic tool, and interrogates whether current AI governance approaches address or reproduce systemic inequities in mental healthcare. Aligning with the conference theme, the objective is to reposition AI governance as a critical lever for addressing root causes of health inequities rather than merely expanding service delivery. |
| Methodology/Approach |
This research employs a qualitative design using discourse and document analysis of policy frameworks, institutional guidance, and academic literature published between 2020 and 2026, with a focus on the post-2022 GenAI expansion. Sources include Canadian federal policy (e.g., AI and data legislation), international guidance (e.g., WHO), and AI developer governance documents. A purposive sampling strategy prioritizes relevance, authority, and recency. Data are analyzed using Fairclough's critical discourse analysis to identify patterns in phrasing related to governance, accountability, leadership, and equity. |
| Results |
Preliminary findings indicate that AI is predominantly positioned as an accessibility-enhancing tool, while upstream determinants, such as regulatory fragmentation, unclear liability, and uneven power distribution between public institutions and private technology firms, remain insufficiently addressed. Policies emphasize ethical principles (e.g., transparency, safety) but lack enforceable mechanisms for equitable implementation. Financial stewardship and leadership gaps further complicate oversight, with limited clarity on who is responsible for harm mitigation in AI-mediated care. |
| Discussion/Conclusion |
AI governance represents a pivotal opportunity to address structural drivers of mental health inequities, yet current approaches risk reinforcing existing disparities by privileging technological scalability over systemic reform. Strengthening governance through enforceable regulation, cross-sector leadership, and equity-centered policy design is essential. Embedding accountability, inclusive decision-making, and public oversight into AI systems can shift the focus from downstream solutions to upstream transformation. Scalable policy frameworks must integrate health equity as a core principle of AI governance, ensuring that technological innovation advances just and inclusive mental healthcare systems. |
| Presenters and Affiliations |
Chloé Currie King's College London (Until August 2026); Balsillie School of International Affairs at the University of Waterloo (September 2026) |
