赛事发布｜AI 社会科学家研究挑战赛：开启AGI时代的社会科学研究之旅

TL;DR - Tsinghua's Computational Social Science and National Governance Lab (with its EE Department) has launched an "AI Social Scientist" research challenge built on the AgentSociety² platform, inviting teams to run large-scale LLM-agent social simulations across seven research tracks. It matters as a concrete push to turn LLM agents from research assistants into full participants in the social-science research pipeline.

• AgentSociety² is pitched as an "Integrated Research Environment for Executable Social Science": it chains question formulation, hypothesis generation, simulation design, mechanism intervention, result analysis, and paper writing into one environment, supporting multi-scale analysis from individual decisions to emergent macro phenomena, plus counterfactual and intervention experiments.
• Seven tracks span public administration/governance, computational political science and digital government, computational law, digital economy, computational communication, computational sociology, and open agent-based CSS exploration — with recurring questions on policy sandboxes, opinion polarization, recommendation-algorithm feedback loops, and human–AI-agent coexistence.
• Logistics: teams of 3–5 (plus 1–2 advisors), all research submissions must run on AgentSociety²; LLM APIs are pre-integrated with ~¥200 starter credit per team. Prize pool is ¥180k (¥80k awards; ¥100k earmarked for API compute).
• Timeline: released 2026-08-08, platform training 8/13, screening 9/15, Q&A 9/17, on-site review and awards tentatively 2026-10-25; strong entries may be recommended to journals such as Journal of Social Computing, ACM TSC, and IEEE TCSS. Judging covers social-science value, novelty, methodological rigor, theoretical contribution, and impact potential.