Discussion Panels

Panel Title: Harnessing Large Language Models for Smarter, More Efficient Cities

Moderator

Hossam Hassanein , Queen’s University, Canada

Panel Overview:

As urban centers grow more digitally intertwined, Large Language Models (LLMs) are revolutionizing how cities approach planning, governance, and community interaction. These AI systems hold transformative promise – from streamlining traffic systems and automating civic services to advancing eco-friendly initiatives. Yet, navigating concerns like data privacy, algorithmic bias, and governance frameworks remains essential. This panel brings together experts from AI research, urban planning, policy-making, and industry to explore how LLMs can shape the future of smart cities responsibly.

Discussion Themes:

1. Streamlining Public Services Delivery – In what ways can LLMs refine citizen-government communication, automate administrative tasks, and deliver instant assistance to communities?
2. AI-Driven Urban Mobility Solutions – How might predictive analytics and intelligent systems reshape transportation networks, emergency protocols, and infrastructure planning?
3. Ethical AI and Data Stewardship – What frameworks ensure transparency, safeguard citizen data, and address biases in urban AI deployments?
4. Sustainability Through AI Innovation – Can LLMs drive smarter energy grids, water conservation, and waste reduction strategies for greener cities?
5. Public-Private Synergy in Tech Adoption – How can industry collaboration accelerate AI integration while balancing governance and commercial interests?
6. Horizons and Hurdles – What emerging opportunities and barriers will define the next era of LLM-powered urban ecosystems?

Agenda:

• Opening Segment (5 min) – Overview of LLMs and smart cities
• Expert Dialogue (45 min) – Panelists discuss key topics and challenges
• Audience Engagement (20 min) – Interactive discussion with attendees
• Final Reflections (5 min) – Key takeaways and future directions