Doug’s career, spanning over two decades, has been a unique blend of public service innovation and entrepreneurial leadership. Currently serving as the Director of Application Management and Enterprise Data at Veterans Affairs Canada, he oversees teams responsible for software development and enterprise data management. This includes specialized teams dedicated to Machine Learning and Automation, all aimed at fulfilling VAC’s critical mission of supporting Canadian Veterans and their families.
Formerly the CEO at Startup Zone, Doug cultivated innovation and growth within Prince Edward Island’s entrepreneurial community. He continues to advise technology startups today and is a regular contributor to open-source projects. He now brings this same spirit of innovation into the realm of the public sector.
Day 1: Oct 14, 2025
1:45 pm
PANEL: AI IN REGULATORY DECISION-MAKING
Building MVPs for AI-Driven Application Processing in Canadian Regulatory Bodies
As regulatory bodies increasingly explore AI for decision-making, developing Minimum Viable Products (MVPs) that align with compliance, transparency, and fairness is critical. Design AI solutions that support regulatory application processing while maintaining public trust. Master the success factors to:
- Leverage past precedents and data analysis to drive efficiency and inform decision-making.
- Ensure transparency, fairness, and explainability in AI-driven decision-making.
- Build cross-functional collaboration among technologists, policymakers, and regulators.
Advance the use of AI to scale efficient and responsible decision-making for Canadian citizens.
Day 2: Oct 22, 2025
8:45 am
OPENING COMMENTS FROM YOUR HOST
Gain insight into today’s sessions so you can get the most out of your conference experience.
11:30 am
PANEL: DATA CULTURES
Designing Teams for Ethical AI — Structure, Skills, and Culture
As AI continues to evolve, so must the teams responsible for building and governing it. Delivering ethical AI at scale requires more than just technical expertise, it demands diverse perspectives, clear accountability, and a culture of continuous reflection. Master the success factors to:
- Assemble cross-functional teams that combine data science, ethics, policy, and subject matter expertise.
- Develop clear systems for enabling
- Define roles and responsibilities to ensure transparency, fairness, and effective governance across AI initiatives.
- Embed ethical considerations into daily decisions through targeted training, thoughtful incentives, and leadership alignment.
Transform your team’s structure to meet growing expectations for responsible AI — and ensure your technology works for people, not just performance
