CIVIC-AI Workshop — July 13

About

CIVIC-AI is a workshop bringing together researchers to examine the interplay between artificial intelligence, work, and society. This inaugural 2026 workshop kicks off the collaboration between Stanford and NUS on these matters, involving policy makers and funding agencies as key collaborators in informing the research agenda and shaping outcomes.

Our central questions:

Cross-cultural Dimensions How do cultural context, economic development, and policy environment shape AI adoption, usage norms, and the lived experience of automation across different societies?
Future of Work & Automation Which professions and tasks are being automated away, and which are being augmented? What does the evidence tell us about the real shape of displacement — and who bears its costs?
Human Advantage What constitutes irreducible human value in a world where a large fraction of knowledge work can be automated? How do we define, measure, and support it?

Programme

All times are in Singapore Time (SGT, UTC+8).

Day 1 · July 13 · Full Day

Theme 1 – Social Intelligence

09:00–09:15 OpeningWelcome & opening remarks

09:15–09:55 Invited TalkInvited Talk 1 — Yohan Jo

09:55–10:35 Invited TalkInvited Talk 2 — Nancy F. Chen

10:35–10:55 BreakCoffee Break

10:55–11:35 Invited TalkInvited Talk 3 — Lizi Liao

11:35–11:55 Lightning TalksLightning Talks Part I — 2 × 10 min

11:55–13:00 LunchLunch

13:00–14:30 KeynoteNAII Keynote — Diyi Yang

14:30–15:30 Lightning TalksLightning Talks Part II — 6 × 10 min

15:30–15:50 BreakCoffee Break

15:50–16:50 PanelPanel

16:50–17:00 ClosingClosing Remarks

Day 2 · July 14 · AM Only

Theme 2 – Future of Work With AI Agents in Singapore

09:00–09:20 OverviewOverview of the space — Diyi

09:20–09:45 PresentationPresentation 1 — Diyi

09:45–10:10 PresentationPresentation 2 — Min

10:10–10:30 BreakCoffee Break

10:30–11:15 DiscussionDiscussion Session 1

11:15–11:25 BreakShort Break

11:25–12:10 DiscussionDiscussion Session 2

12:10–12:30 ClosingFinalizing Directions & Next Steps

Invited Speakers

KEYNOTE

Diyi Yang

Stanford Univ.

Optimizing Human-AI Collaboration

Recent advances in large language models (LLMs) have transformed human-AI interaction, however, building effective collaboration requires AI systems that truly understand the people they work with. In this talk, we first audit the U.S. workforce to assess the impact of automation and augmentation on the future of work, guiding the development of AI agents that reflect workers' perspectives. We then introduce General User Models (GUMs), which learn about users by observing any computer interaction and constructing propositions about user knowledge, preferences, and context. We further present NAP (Next Action Prediction), a framework for anticipating user intent by reasoning over rich multimodal sequences of human-computer interactions, where modeling long interaction histories enables significantly more accurate predictions. Overall, this talk highlights how to develop AI systems that are proactive and capable of fostering meaningful collaboration with human users.