2026 DTI Symposium

Rabi Parhizkari’s research examines how research funding priorities shape the direction of knowledge production and influence broader understandings of peace, security, and public value. Using NSERC funding data, her project analyses funding patterns across selected programmes and research categories, with attention to how institutional support is distributed across different areas of inquiry. By combining data analysis with keyword extraction methods, her work explores the relationship between funding structures, research agendas, and the social meanings attached to scientific and technological development. This project raises important questions about how public resources shape research priorities and how concepts such as defence, innovation, and peace are framed within research policy.

Acassia May Arnaud’s research examines why AI policy needs to engage more directly with human rights, equity, and sustainable development. Her project considers how AI systems can affect the environment, social inequality, disadvantaged economies, and socio-economic groups, while also shaping progress toward the Sustainable Development Goals. By analysing the relationship between AI governance, EDI, and SDG-related policy priorities, her work raises important questions about how AI regulation can respond to both technological risks and broader social responsibilities. This project contributes to discussions about responsible AI policy, human-centred governance, and the need to ensure that AI development supports public value rather than reinforcing existing inequalities.

Ata IzakShiri’s research examines the concentration of innovation within the artificial intelligence sector through a bibliometric analysis of corporate patents and publications. Drawing on patent datasets and scholarly publication records, his project investigates how major firms contribute to and shape AI development. The study focuses on patterns of ownership concentration, AI specialization, and collaboration among leading corporate actors. By comparing diversified technology portfolios with more specialized AI strategies, his work raises important questions about oligopolistic control, competitive advantage, and the distribution of knowledge production in AI innovation.

The presentations reflected the range of research being developed within the Parallel Science Lab, from AI policy and research funding to innovation systems and the social implications of digital transformation. The lab is especially pleased to celebrate Acassia May Arnaud’s achievement in receiving the Early Stage Award in the Master’s category. This recognition highlights the promise of her research on AI policy and human rights, as well as the importance of student-led scholarship that examines how digital technologies can be governed in more equitable, accountable, and socially responsible ways