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Intersectional Biases in Generative Language Models and Their Psychosocial Impacts | Stanford HAI
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eventSeminar

Intersectional Biases in Generative Language Models and Their Psychosocial Impacts

Status
Past
Date
Wednesday, October 16, 2024 12:00 PM - 1:15 PM PST/PDT
Location
Hybrid
Topics
Ethics, Equity, Inclusion
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Overview
Event Recording

HAI Seminar with Faye-Marie Vassel & Evan Shieh

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Event Contact
HAI Events Team
stanford-hai@stanford.edu
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Abstract: 

The rapid emergence of generative AI technologies has been shaped by a wave of early excitement and hope for a broad range of use cases. Yet, the impacts of the latest models on historically marginalized communities is still relatively understudied, including the potential for sociotechnical harm.

In this session, the speakers present a line of research uncovering intersectional biases in generative language models when they are used for open-ended writing, drawing connections between their synthetic text outputs and known linguistic patterns that have psychosocial impacts for diverse learners in educational settings.

Speakers
Evan Shieh
Executive Director and AI Researcher, Young Data Scientists League
Faye-Marie Vassel
STEM Education, Equity, and Inclusion Postdoctoral Fellow