NLP Seminar: Weixin Liang, Societal Impact of Large Language Models

Content

Speaker

Weixin Liang (Stanford University)

Abstract

Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society. This talk examines how individuals and institutions are adapting to and engaging with this emerging technology through three research directions. First, I demonstrate how the institutional adoption of AI detectors introduces systematic biases, particularly disadvantaging writers of non-dominant language varieties, highlighting critical equity concerns in AI governance. Second, I present novel population-level algorithmic approaches that measure the increasing adoption of LLMs in academic writing, revealing consistent patterns of AI-assisted writing across diverse academic fields in both peer reviews and publications. Finally, I investigate LLMs' capability to provide feedback on research manuscripts through a large-scale empirical analysis, offering insights into their potential to support researchers who face barriers in accessing timely manuscript feedback, particularly early-career researchers and those from under-resourced settings.

Bio

Weixin Liang is a final-year Computer Science Ph.D. candidate at Stanford University, where his research focuses on understanding and shaping the societal impact of large language models. His work spans three main research thrusts: investigating the societal adoption and implications of AI-assisted writing, developing sustainable AI through efficient language model architectures, and advancing responsible AI development through data-centric approaches. His recent research has revealed widespread adoption of large language models across academic, corporate, and government communications, leading to a Best Presentation Runner-up Award at ICSSI (International Conference on the Science of Science and Innovation) 2024 at the National Academy of Sciences. His research has been featured in over 300 media outlets worldwide, including Nature, The New York Times, Scientific American, The Guardian, and Fortune.

Faculty host

Andrew McCallum