Dr Fanqi Zeng, University of Oxford
Department of Sociology (42-43 Park End Street) or MS Teams
Please join either in person or online. For in-person attendees, the talk will be preceded by a light lunch at 12.15pm.
Please email comms@sociology.ox.ac.uk with any questions.
Abstract
AI is reshaping sociology both as an object of inquiry and as a methodological resource. This talk examines this dual transformation through two complementary perspectives. First, drawing on a comparative analysis of elite sociology departments, faculty profiles, and national sociology conferences in China and the United States, it traces how AI has been incorporated into sociological knowledge production across different institutional and societal contexts in recent years. The analysis reveals both divergent and convergent trajectories, highlighting how scholars in the Global North and Global South engage with AI in distinct yet increasingly interconnected ways.
Second, the talk demonstrates the research potential of AI for sociology through an original case study modelling future societal instability across four countries. By integrating demographic and fiscal data with large language models, we develop and evaluate predictions concerning the structural constraints facing welfare states through the mid-twenty-first century. Together, these analyses illustrate how AI is transforming what sociologists study, how they study it, and what futures we might anticipate.
Biography
Fanqi is a UKRI Metascience AI Early Career Fellow in the Department of Sociology and a Junior Research Fellow at Wolfson College. His research bridges AI and the social sciences, harnessing computational methods and large-scale data to illuminate patterns within complex societal and natural systems. His current work explores the transformative impact of AI on society and human behaviour.
Prior to his current role, he was a Postdoctoral Fellow in the same department, working in parallel on the Wellcome Trust–funded FORESFA project on global substandard and falsified medicines and the European Research Council–funded CrimGov project on global organised crime and governance. His research has appeared in leading interdisciplinary journals, including Science, Nature Cities, Nature Communications, PNAS, and PNAS Nexus.
He holds a PhD in Engineering Mathematics from the University of Bristol, completed under the supervision of Professors Thilo Gross, Martin Homer, and Nikolai Bode. His doctoral research employed a combination of top-down (model-driven) and bottom-up (data-driven) approaches, drawing on machine learning, agent-based modelling, and network science to investigate complex systems.
