Designed as an actionable extension of the UNU Macau AI Conference 2026, The AI × Education Workshops and Training translate our thematic discourses into highly practical, immersive learning sessions.

The training stream will feature 6–9 interactive workshop sessions, each running for 2 hours, designed to provide practical learning opportunities for educators, students, policymakers, industry professionals, and civil society representatives, while also showcasing innovative AI applications and talent development initiatives.

UNU Macau AI Conference 2026

November 26 · Agenda at a Glance

9:00-
12:30

AI for SDGs -
Global Youth AI Future Innovation Competition 2026
Final Round

AI × Education
Workshop Sessions 1-6

12:30-
14:00

Networking Lunch

14:00-
15:00

Joint Plenary Keynote Sessions

15:30-
17:30

AI for SDGs -
Global Youth AI Future Innovation Competition 2026
Award Ceremony

AI × Education
Workshop Sessions 7-9

Workshop tracks, topics, facilitators and descriptions (tentative)

Track: Education & Learning Innovation

Critical Thinking in the Age of AI	Dr. Rachel Um, Executive Director of Teaching and Learning, Continuing Education Division of Harvard University	Explore practical strategies for developing learners’ critical thinking skills, enabling them to evaluate information, question assumptions, construct evidence-based arguments, and engage responsibly with AI in the digital age.
Building AI Literacy through Computational Thinking	Dr. Ting YUAN, Associate Professor, Department of Curriculum and Instruction, City University of New York	Explore how unplugged computational thinking activities can help learners understand the foundations of machine learning and develop essential AI literacy skills through interactive, hands-on experiences.
From AI Claims to Meaningful Learning: Designing Responsible Learning Experiences for K-12 Education with UbD and Generative AI	Dr. Zhou ZHOU, Learning Sciences and AI in Education Expert, Innovation Fellow at Columbia University	Explore how learning sciences, Understanding by Design (UbD), and generative AI can be combined to create meaningful learning experiences that promote student agency, critical thinking, and responsible AI use.
Designing Reproducible LLM Workflows for Research	Jiaan LIU, Research Assistant, UNU Macau	Learn how large language models and agentic AI can support structured research workflows for analysing unstructured data, while exploring practical applications using UNU Macau’s Tessera platform.
Supporting Educators and Institutions in AI Integration	Dr. Andreia Inamorato Dos Santos, Universidad Loyola, International Council for Open and Distance Education	Explore practical approaches to building educator capacity, institutional readiness, and governance frameworks for the responsible integration of AI across teaching, learning, assessment, and organizational practice.

Track: Technology, Society & Policy

Agentic AI: From Technical Foundations to Real-World Applications	Thomas BASIKOLO, Programme Officer, ITU Telecommunication Standardization Bureau (TSB)	Discover how agentic AI is transforming artificial intelligence from passive assistants into autonomous systems, and explore its emerging applications, opportunities, limitations, and governance challenges across sectors.
Global AI Governance	Professor Yik Chan Chin, UNU Macau	Explore the evolving global AI governance landscape and examine key challenges including AI safety, standards, international coordination, and responsible implementation across sectors.
AI for Social Impact Organisations	Andressa Trivelli, Canal Sabiar	Discover a practical, impact-first framework for helping nonprofit and social impact organisations adopt AI responsibly while strengthening organisational effectiveness, innovation, and community impact.
AI-Assisted Decision Support for Policymakers	Visiting Fellows, UNU Macau	Explore frontier AI tools developed at UNU Macau that support evidence-informed policymaking, inclusive deliberation, and human-AI collaboration for complex policy challenges.

Track: Simulation & Applied Learning for Youth

Remodel UN: AI-Powered Model UN Simulations	Jiaan LIU, Research Assistant, UNU Macau	Experience Model UN in a new AI-supported, research-linked format where participants investigate real-world governance challenges, evaluate evidence, and develop practical policy recommendations through research, simulation, and negotiation.
AI Governance Policy Comparative Lab	Dr. Farhan Latif, Postdoctoral Fellow; Yuanyuan LI, Research Fellow, UNU Macau	Explore how countries and regions approach AI governance through a comparative policy analysis framework developed by UNU Macau, using collaborative analysis, negotiation, and consensus-building activities.
Bridging Conservation AI and Education: Empowering the Next Generation for Sustainability	WWF - HK Education Team	Explore how AI is being applied to real-world conservation challenges and discover ways to foster AI literacy, critical thinking, and sustainability awareness through education.