AI.X Seminar 22 July 2026

Title: Building AI Agents that Augment Human Work

Speaker: Professor Diyi Yang, Stanford University

Time: July 22, 2026 (Wed), 3:30pm – 4:30pm

Venue: LT5

Abstract:  Recent advances in large language models (LLMs) have transformed human-AI interaction, however, building effective collaboration requires AI systems that truly understand the people they work with. In this talk, we first audit the U.S. workforce to assess the impact of automation and augmentation on the future of work, guiding the development of AI agents that reflect workers' perspectives. We then introduce General User Models (GUMs), which learn about users by observing any computer interaction and constructing propositions about user knowledge, preferences, and context. We further present NAP (Next Action Prediction), a framework for anticipating user intent by reasoning over rich multimodal sequences of human-computer interactions, where modeling long interaction histories enables significantly more accurate predictions. Overall, this talk highlights how to develop AI systems that are proactive and capable of fostering meaningful collaboration with human users.

Bio:  Diyi Yang is an assistant professor in the Computer Science Department at Stanford University, also affiliated with the Stanford NLP Group, Stanford HCI Group and Stanford Human Centered AI Institute. Her research focuses on human-centered natural language processing and human-AI interaction.  She is a recipient of  IEEE “AI 10 to Watch” (2020), Microsoft Research Faculty Fellowship (2021),  NSF CAREER Award (2022), an ONR Young Investigator Award (2023), and a Sloan Research Fellowship (2024).  Her work has received multiple paper awards or nominations at top NLP and HCI conferences.