UCLA DataX Symposium on Data Science Education: Building Bridges from K-12 to Beyond

We are pleased to invite you to attend the keynote address of the UCLA DataX Symposium on Data Science Education: Building Bridges from K-12 to Beyond. Thema Monroe-White (George Mason University) and Evan Shieh (Young Data Scientists League) will present " From Algorithmic Biases to Critical AI Literacy".  

Light refreshments will follow the talk.

Abstract: As AI tools accelerate into classrooms and workplaces, many of students are expressing anxiety about what these technologies will mean for their futures. While teaching AI literacy in K-12 contexts, not only did we observe “bias” in large language models, we observed an amplification of entrenched power imbalances where racialized, gendered, and sexualized hierarchies were reproduced and intensified through seemingly innocuous writing tasks. These patterns prompted a collaborative, student-centered research agenda that culminated in an AI experiment systematically probing how leading models from OpenAI, Google, Meta, and Anthropic generate harmful and stereotypical narratives of minoritized identities. Our findings demonstrate that these outputs disproportionately target minoritized students, but also harm non-minoritized students by normalizing inequitable ways of interacting, imagining, and collaborating, ultimately undermining the development of real-world learning and work environments.

What does it mean for data science education when teaching AI risks reinscribing the very inequities we are working to dismantle? How might we combat these power imbalances by drawing on the legacies of past and current critical algorithmic and education scholars who teach us to interrogate, refuse, and reimagine oppressive technologies? As we consider how to cultivate future generations of AI-literate citizens within the goals of Data X Presents: Symposium on Shaping the Future of Data Science Education—Building Bridges from K-12 to Beyond, this talk offers both caution and possibility for building more empowering sociotechnical futures.

Bio: Thema (Tay-mah) Monroe-White is an Associate Professor of Artificial Intelligence and Innovation Policy in the Schar School of Policy and Government and the Department of Computer Science at George Mason University. She is particularly concerned with understanding the pathways to achieving social and economic uplift for minoritized groups via AI education, and emancipatory data practices in which critical quantitative and computational approaches are used to challenge algorithmic biases, advance racial equity, and reimagine data systems for the empowerment of marginalized communities.

Bio: Evan Shieh works as an AI researcher and educator focusing on culturally relevant data science and AI justice. In his current role as Executive Director at the Young Data Scientists League, Evan has reached thousands of minoritized students and educators of color in urban and rural communities that traditionally lack power and pathways to tech. Previously, Evan led teams of AI scientists at big tech companies to study and evaluate multilingual language models using critical machine learning research.