Challenges and Progress Towards Socially Responsible Natural Language Processing

Tuesday, May 23, 2023
12:00 PM - 1:00 PM
(Pacific)

Encina Commons, Moghadam 123

headshot of diyi yang with text reading spring seminar series on green background

Join the Cyber Policy Center, together with the Program on Democracy and the Internet for Challenges and Progress Towards Socially Responsible Natural Language Processing, a conversation with Diyi Yang, moderated by Jeff Hancock, co director of the Stanford Cyber Policy Center. This session is part of the Spring Seminar Series, a series spanning April through June, hosted at the Cyber Policy Center with the Program on Democracy and the Internet. Sessions are in-person and virtual, with in-person attendance offered to Stanford affiliates only. Lunch is provided for in-person attendance and registration is required.

Despite the remarkable performance of NLP these days, current systems often ignore the social part of language, e.g., who says it, or what goals, and with what social implications, all of which severely limits the functionality of these applications and the growth of the field. This talk will discuss some recent efforts towards socially responsible NLP via two studies. The first part looks at linguistic prejudice with a participatory design approach to develop dialect-inclusive language tools for low-resourced dialects. The second one examines opportunities and risks associated with zero-shot reasoning in large language models when it comes to analyzing social phenomena. Yang conclude by discussing the challenges and hidden risks of building socially responsible AI systems.

This session will take place in Encina Commons, Moghadam 123.

About the Speaker:

Diyi Yang is an assistant professor in the Computer Science Department at Stanford University.  Her research goal is to understand the social aspects of language and build socially responsible NLP systems for social impact. Her work has received multiple best paper nominations or awards at top NLP and HCI conferences (e.g., ACL, EMNLP, SIGCHI, and CSCW).  She is a recipient of  IEEE “AI 10 to Watch” (2020), the Intel Rising Star Faculty Award (2021), the Samsung AI Researcher of the Year (2021), the Microsoft Research Faculty Fellowship (2021),  and the NSF CAREER Award (2022).