I2SC Lecture Series (Recording): Vagrant Gautam (Computer Science, Saarland University), On Gender Gaps in Natural Language Processing

Date: May 10, 2024

Abstract: In the field of natural language processing (NLP), gender gaps are thought of and treated similarly to the gender wage gap in economics. I will present previous work on the Gender Gap Tracker at Simon Fraser University and more recent work done at Saarland University on pronoun use with large language models, to illustrate how gender gaps are technically operationalized in NLP. These examples will serve as motivation to discuss bigger-picture epistemological gaps in how “gender” is treated in NLP - typically as binary, immutable, and directly inferable from characteristics such as a person’s name, pronouns, and so on. Drawing on methodologies, frameworks and viewpoints from other disciplines, including work I was involved in on the use of intersectionality in AI fairness, I will end with my thoughts and hopes for closing the epistemological gaps, with the goal of addressing the technical gaps more effectively and justly.

You can watch the recording of the talk below. 


 


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