Intersectional Biases in Generative Language Models and Their Psychosocial Impacts
HAI Seminar with Faye-Marie Vassel & Evan Shieh
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HAI Seminar with Faye-Marie Vassel & Evan Shieh
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.
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.

