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CDL Seminar: Can Generative AI improve social science?
Join on MS Teams: teams.microsoft.com/l/meetup-join/19%3aH7IoYwBLlY_nR8d0DFzqC4yXRigyhbzyOceuytRk4g01%40thread.tacv2/1728553869256?context=%7b%22Tid%22%3a%22cc95de1b-97f5-4f93-b4ba-fe68b852cf91%22%2c%22Oid%22%3a%22be558437-bc8f-4f3b-801c-af85d95b70ea%22%7d
Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the potential to improve survey research, online experiments, automated content analyses, agent-based models, and other techniques commonly used to study human behavior. In the second section of this article, I discuss the many limitations of Generative AI. I examine how bias in the data used to train these tools can negatively impact social science research—as well as a range of other challenges related to ethics, replication, environmental impact, and the proliferation of low-quality research. I conclude by arguing that social scientists can address many of these limitations by creating open-source infrastructure for research on human behavior. Such infrastructure is not only necessary to ensure broad access to high-quality research tools, I argue, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.
Date:
11 February 2025, 17:00
Venue:
15 Norham Gardens, 15 Norham Gardens OX2 6PY
Venue Details:
MS Teams
Speaker:
Professor Christopher Bail (Duke University, USA)
Organising department:
Department of Education
Organiser:
Dr Sara Ratner (University of Oxford)
Part of:
Child Development and Learning Research Group Seminars
Booking required?:
Not required
Audience:
Public
Editors:
Hannah Freeman,
Heather Sherkunov,
Kristina Khoo
