City University of Hong Kong
Computational Social Science Lab
Department of Public and International Affairs
City University of Hong Kong
CityUHK CSSL

The Inaugural Annual Conference on AI, Large Language Models, and the Social Sciences (LLMSS 2026)

LLMSS 2026 — The Inaugural Annual Conference on AI, Large Language Models, and the Social Sciences, 13–16 October 2026, Senate Room, 19/F, Lau Ming Wai Academic Building, City University of Hong Kong

Date: 13–16 October 2026 (workshops on 13 October; main conference 14–16 October)
Venue: Senate Room, 19/F, Lau Ming Wai Academic Building, City University of Hong Kong
Organised by: Computational Social Science Lab (CityUHK) · Talking to Machines (Nuffield College, University of Oxford) · Analytics Lab for Global Risk Politics (Peking University)

LLMSS 2026 brings together AI researchers, industry practitioners, government representatives, and social scientists to examine how large language models are reshaping research methodologies, data analysis, and theoretical frameworks across the social sciences. The programme features keynote talks, paper and poster sessions, interactive workshops, methodological demonstrations, and five roundtables.

Full conference programme

Keynote Speakers

Prof. Zhongyu Wei

Zhongyu Wei

Professor, School of Data Science, Fudan University

“SocioVerse 2.0 — A Longitudinal Dynamic Social Simulation Framework”

Wednesday 14 October, 2:00–3:00 PM · Senate Room

Prof. Meng Tianguang

Meng Tianguang

Tenured Professor of Political Science; Associate Dean, School of Social Sciences, Tsinghua University

“Inside-the-State Legibility: AI Simulation and the Black Box of Government Responsiveness in China”

Thursday 15 October, 9:00–10:00 AM · Senate Room

Prof. Issa Dahabreh

Issa Dahabreh

Associate Professor of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health

Thursday 15 October, 2:00–3:00 PM · Senate Room

Prof. Scott A. Hale

Scott A. Hale

Professor of Social Data Science & Director, Oxford Internet Institute, University of Oxford

“Equitable Access to Quality Information and Generative AI”

Friday 16 October, 9:30–10:30 AM · Senate Room

Pre-Conference Workshops — Tuesday 13 October

A full-day, hands-on, code-along programme on applied AI/LLM methods for the social sciences:

  • AIPOP — Artificially Intelligent Public Opinion Polling (Raymond Duch & Matias Fuentes Becerra), 09:00–12:30
  • Predicting Human Behavior with LLMs — A Practical Toolkit for Valid Inference (David Broska), 09:00–12:30
  • Talking to Digital Twins — The Wisdom of Digital Twins (Raymond Duch & Matias Fuentes Becerra), 13:30–15:30
  • The Silicon Audience: Designing Persuasive Messages, from Campaigns to Courtrooms (Raymond Duch & Laurenz Guenther), 15:45–17:45

Roundtables

  • When Do LLM Simulations Become Evidence About People? (14 Oct)
  • The Risks of AI: Should We Slow Down? (15 Oct)
  • Industry, China and Open-Weight Models (15 Oct)
  • Beyond the Black Box: Interpretation, Meaning, and Human Understanding in AI-Driven Social Research (plenary roundtable, 15 Oct)
  • Can AI Understand Society? Transdisciplinary Dialogues on the Future of Social Science Education (16 Oct)