CIIR Talk Series: Qiaozhu Mei

Speaker: Qiaozhu Mei, University of Michigan

Title: Beyond the Behavioral Turing Test: Initial Steps Towards an AI Behavioral Science


Do Large Language Models (LLMs) possess personality traits, and do their behaviors differ from human ones? Exploring the preferences and behaviors of LLMs to ensure alignment with human values is crucial for facilitating effective human-AI collaboration and maximizing societal benefits. As a foundational step towards an AI behavioral science, we introduce a behavioral Turing test that contrasts the behavioral traits of LLMs against those of hundreds of thousands of human participants. In the second part of the talk, we explore a methodology teaching LLMs to generate content tailored to the specific context of a user, drawing on principles from writing education.


Qiaozhu Mei a professor in the School of Information and the College of Engineering at the University of Michigan, where he served as the founding director of the Master of Applied Data Science program. His research group develops novel methods in machine learning, data mining, information retrieval, and natural language processing and applies them to diverse domains, such as the Web, social media, healthcare, and education. His work has received multiple best paper awards at ICML, WWW, WSDM, KDD, and other major conferences in computing. Qiaozhu is an ACM Distinguished Member. He has served as the General Co-Chair of ACM SIGIR 2018 and currently serves on the editorial board of the Journal of Machine Learning Research, the ACM Transactions on the Web, and the IEEE Transactions on Big Data.

Date: Friday, March 29, 2024 - 1:30 - 2:30 PM EDT (North American Eastern Daylight Saving Time) via Zoom. On campus attendees will gather in CS 151 to view the presentation.

Zoom Link: Subscribe to mailing list (details at for Zoom Link/Passcode notifications; or click here for Zoom link and reach out to Hamed Zamani or Alex Taubman for the passcode.