Friday / CS Seminar

February 13th / 12:00 PM

Hybrid / Mudd 3514

Speaker

Kaitlyn Zhou, Stanford University

Talk Title

Broadening AI Utility Through Natural Language Interfaces

Abstract

In this talk, I will present the novel dynamics of human interaction with large language models (human-LM interaction), focusing on how these systems shape human decision-making, trust, and reliance. As the world seeks to integrate the innovations of foundation models into everyday work and life, my mission is to design human-centered natural language interfaces to augment human intelligence and democratize access to AI. My work pioneers key advancements in natural language processing and human-computer interaction by: 1) uncovering core algorithmic risks in current human-LM interactions, 2) articulating the factors that complicate human-AI interactions, and 3) proposing new human-LM interactions to serve the needs of a broader population.

Biography

Kaitlyn Zhou is PhD candidate in computer science at Stanford University, advised by Dan Jurafsky. Her contributions have been recognized at top-tier conferences in NLP and HCI. She has received awards such as MIT EECS Rising Star, Stanford Graduate Fellowship, and the College of Engineering Dean's Medal, and her methods have been featured in high-profile news outlets like the New York Times and Wall Street Journal. Kaitlyn has long advocated for increased access, inclusion, and equity in higher education and was appointed by the Washington State Governor to serve on the University of Washington Board of Regents.

Research/Interest Areas

natural language processing, human-computer interactions

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Zoom: https://northwestern.zoom.us/j/98362439009?pwd=c89YlFRcBHSe1XH0PEl5rKu0HtuRpA.1

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6719566d-cf13-45ec-a0f3-b27b0117b56e

Community Connections Topic: Black History Month