Events
FDS Colloquium
Harnessing AI and Digital Data: Unlocking New Frontiers in Family Research
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Speaker: Emma Zang Assistant Professor of Sociology, Biostatistics (Secondary) and Global Affairs (Secondary) Wednesday, October 23, 2024 11:30AM - 1:00PM Lunch at 11:30am in room 1307
Talk at 12:00pm in room 1327 Location: Yale Institute for Foundations of Data Science, Kline Tower 13th Floor, Room 1327, New Haven, CT 06511 and via Webcast: https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=88d65045-27d8-4e5e-acda-b21000f6c251 |
Abstract: AI and digital data have been increasingly used to explore a wide range of social science topics, yet their potential in family research remains largely untapped. I will present two of my projects that leverage these tools to offer new insights into family dynamics. The first project, Remote Work and Utilization of Formal Childcare Services, uses anonymized mobile location data from SafeGraph and Facebook Movement Range to analyze how remote work is associated with the utilization of formal childcare services (i.e., childcare centers, and primary and secondary schools). We further examine how this relationship varies by the availability, affordability, and quality of these services. The second project, Evaluating LLMs for Chinese Divorce Judgments, tests the capabilities of large language models (LLMs) including a range of GPT models (GPT-3.5, GPT-4, GPT-4o-mini, GPT-4o, and a fine-tuned GPT-4o-mini) and a Chinese LLM, Qwen, to classify over 1.5 million Chinese divorce cases by variables such as gender, custody claims, and property disputes. It compares AI-based methods with traditional machine-learning approaches in this legal context. These projects illustrate the untapped potential of AI and digital data to deepen our understanding of family dynamics, opening new avenues for research in this field.
Speaker bio: Dr. Emma Zang is an Assistant Professor in the Department of Sociology at Yale University, with secondary appointments in Biostatistics and Global Affairs. Her research interests intersect at the nexus of health and aging, family demography, and inequality, employing advanced data science and statistical tools. She also develops and evaluates statistical methods to model trajectories and life transitions, aiming to understand health disparities from a life course perspective. Her research has received media coverage from over 500 outlets in the United States, China, South Korea, India, and Singapore. Her work has received multiple academic awards from organizations such as the American Sociological Association and IPUMS USA.
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