Keynote Speakers

Abstract: AI increasingly shapes governmental decision-making both locally and across political boundaries: who obtains a visa, who is surveilled, or who obtains services. How do we best govern AI? Around the world, AI governance models have been top-down, run by government officials and technical elites, and rely on “soft law” of internal ethics reviews or external impact assessments, muting the voices of those most impacted. I will describe participatory AI governance (PAIG) as a model to design and deploy AI with and not just for communities. I will explore how activities such as participatory design and budgeting, third-party audits, and community-centered impact assessments can begin to define a PAIG model to reduce collective harm and build community trust. Importantly, this PAIG is bottom-up and embeds political power and influence, which often is neglected or resisted by government and tech evangelists. Therefore, the model includes methods to resist or halt AI systems. It includes acknowledgement that certain communities have legitimate reasons to distrust status quo AI and need to assume control of these technologies. Ultimately, PAIG is not just about doing AI for good (or responsibly, safely or securely)—it’s about doing AI for social justice that truly benefits communities.

Bio: Dr Renée Sieber is an associate professor at McGill University. She has 20+ years experience working at the intersection of civic empowerment and computational technologies. She is best known for her research and practice on public participation in computerized mapping and in climate modeling. She currently researches public participation in AI. She  advised the design of two AI risk assessment tools and led the public participation subgroup of the IEEE working group on AI procurement. For the past 5 years, she has co-hosted the monthly community of practice on AI in Canadian Municipalities. This year she was named 2025’s 100 brilliant women in AI Ethics.