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Event Detail

The Hierarchy of Knowledge in Machine Learning and Related Fields and Its Consequences

Wednesday, April 14, 2021 | 12 p.m. - 1 p.m.

    Location
  • Zoom

Feminist and race and gender scholars have long critiqued "the view from nowhere" that assumes science is "objective" and studied from no particular standpoint. In this talk, Dr. Timnit Gebru discusses 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 her own life, education and current work, Dr. Gebru shares how this knowledge hierarchy limits the field and potential ways forward.

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This event is part of an ongoing lecture series "The Future is Intersectional: Black Women Interrogating Technology," organized by the Spelman College Center of Excellence for Minority Women in STEM, in collaboration with the Atlanta University Center Data Science Initiative, UCLA Center for Critical Internet Inquiry and Mozilla.


ABOUT Timnit Gebru, Ph.D.

Timnit GebruUntil she recently got fired, Dr. Timnit Gebru co-lead the Ethical Artificial Intelligence research team at Google, working to reduce the potential negative impacts of AI.

Dr. Gebru earned her doctorate under the supervision of Fei-Fei Li at Stanford University in 2017 and did a postdoc at Microsoft Research NYC in the FATE team. She is also the cofounder of Black in AI, a place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence.

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