Generative AI & Computational Social Science
📋 Research Overview
This theme investigates how large language models (LLMs) and multimodal AI systems are transforming research methodology, public institutions, and labor markets. CTDS faculty use LLMs as measurement instruments, study algorithmic fairness and AI bias (including in peer review and credit allocation), apply multimodal AI to recover legacy effects of historical policy decisions such as redlining, and model the economic and labor market consequences of AI adoption across U.S. metropolitan areas. Methods include machine learning, deep learning, natural language processing, geospatial AI, and agent-based simulation. This work is supported by national funders including Anthropic and the Korea National Research Foundation, and draws on collaborations with Hanyang University (Seoul) and other international partners.
💰 External Funding
Economic Futures Grant - Impacts of AI on Local Labor Markets
Anthony Howell (PI). Modeling how AI adoption affects local labor markets, skill premiums, occupational displacement, and economic resilience across U.S. metropolitan areas.
Generative AI for Sustainable Environmental Planning
Yushim Kim, Anthony Howell, Elizabeth Corley, and Spiro Maroulis. Investigates how generative AI tools can support environmental planning, sustainability governance, and policy analysis in urban contexts.