Abeba works as a senior research fellow at the Mozilla Foundation, where she researches human behaviour, social systems, and responsible and ethical artificial intelligence (AI). Abeba Birhane is an Ethiopian-born cognitive scientist who works at the intersection of complex adaptive systems, machine learning, algorithmic bias, and critical race studies. In her present work, Abeba examines the challenges and pitfalls of computational models and datasets from a conceptual, empirical, and critical perspective. Abeba’s fellowship focuses on auditing canonical datasets as well as exploring ways to clean and detoxify large scale datasets, including the governance models needed to maintain and manage those datasets.

Abeba Birhane has a PhD in cognitive science at the School of Computer Science, UCD, and Lero, The Irish Software Research Centre. Her interdisciplinary research focused on the dynamic and reciprocal relationship between ubiquitous technologies, personhood, and society. Specifically, she explored how ubiquitous technologies constitute and shape what it means to be a person through the lenses of embodied cognitive science, complexity science, and critical data studies.

Her work with Vinay Prabhu uncovered that large-scale image datasets commonly used to develop AI systems, including ImageNet and 80 Million Tiny Images, carried racist and misogynistic labels and offensive images. She has been recognised by VentureBeat as a top innovator in computer vision.

Recent publications:

Birhane, A., Isaac, W., Prabhakaran, V., Diaz, M., Elish, M. C., Gabriel, I., & Mohamed, S. (2022). Power to the People? Opportunities and Challenges for Participatory AI. EAAMO ’22: Equity and Access in Algorithms, Mechanisms, and Optimization(6), 1-8

Newman, S., Birhane, A., Zajko, M., Osoba, O. A., Prunkl, C. Lima, G., et al. (2019). AI & Agency. UCLA: The Program on Understanding Law, Science, and Evidence (PULSE).https://escholarship.org/uc/item/8q15786s 

 

 

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