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Stanford Seminar - Replication strategies for more robust human simulation

May 17, 2024 Aaron Shaw, Northwestern University Increasingly, Large Language Models (LLMs) are used to simulate human behavior and social systems. However, despite rapidly growing scientific and commercial applications of LLMs along these lines, threats to the validity and robustness of such applications remain poorly understood and responses to these threats remain ad hoc. Replication strategies inspired by prior social science and statistical research offer insights into these challenges. This talk characterizes some key threats to LLM simulations of human behavior and explores two strategies---perturbation and iteration---to evaluate LLM simulations of human behavior in the context of social scientific replication. About the speaker: Aaron Shaw is Associate Professor of Communication Studies and Sociology (by courtesy) at Northwestern University and a Faculty Associate of the Berkman Klein Center for Internet and Society at Harvard University. He is a co-founder of the Community Data Science Collective. Around Northwestern, he is also affiliated with the Center for Human-Computer Interaction + Design (HCI+D), the Institute for Policy Research, and the Buffett Institute for Global Affairs. More about the course can be found here: https://hci.stanford.edu/seminar/ View the entire CS547 Stanford Human-Computer Interaction Seminar playlist:    • Stanford CS547 - Human-Computer Inter...   ► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore