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"The hierarchy of knowledge in machine learning & related fields and its consequences" Lecture by Dr. Timnit Gebru
Feminist and race & gender scholars have long critiqued "the view from nowhere" that assumes science is "objective" and studied from no particular standpoint. In this talk, I discuss how this view has resulted in a hierarchy of knowledge in machine learning and related fields, devaluing some types of work and knowledge (e.g. those related to data production, annotation, and collection practices) and mostly amplifying specific types of contributions. This hierarchy also results in valuing contributions from some disciplines (e.g. Physics) more than others (e.g. race and gender studies). With examples from my own life, education, and current work, I discuss how this knowledge hierarchy limits the field and potential ways forward.

Oct 5, 2021 04:00 PM in Pacific Time (US and Canada)

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