Seyi Olojo

Seyi Olojo is PhD student in the School of Information with a designated emphasis in Science and Technology Studies at The University of California, Berkeley. Her research explores how colonial histories of racial classification are re-articulated within contemporary machine learning practices, specifically data collection and early-stage machine learning. Additionally, she investigates the relationship between technical failures and identity formation among historically marginalized communities.

Most recently, she wrote about the role of Western values in the mistranslation of indigenous Nigerian languages for commercial machine translation technologies. Seyi’s current project uses both an ethnographic and theoretical approach to examine how counter epistemologies resist algorithmic violence and challenge political suppression, creating critical and community-based methods for machine learning practice.

Her research has been published in Frontiers of Psychology, ACM Computer- Supported Cooperative Work, and an edited Data & Society keywords anthology on the “The Datafied State”. Her research is supported by the U.S. National Science Foundation, the Eugene Cota-Robles Fellowship, the U.S. Fulbright Program, and the Weizenbaum-Institute for Networked Society.