Coded Bias (10/1/24)
Tuesday October 1, 2024 | 5:30-8:00 PM | Capen Hall 310
Coded Bias explores the fallout of MIT Media Lab researcher Joy Buolamwini’s discovery that facial recognition does not see dark-skinned faces accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all.
Modern society sits at the intersection of two crucial questions: What does it mean when artificial intelligence increasingly governs our liberties? And what are the consequences for the people AI is biased against? When MIT Media Lab researcher Joy Buolamwini discovers that many facial recognition technologies do not accurately detect darker-skinned faces or classify the faces of women, she delves into an investigation of widespread bias in algorithms. As it turns out, artificial intelligence is not neutral, and women are leading the charge to ensure our civil rights are protected.
Directed by Shalini Kantayya. Documentary.
About the speakers
E. Bruce Pitman is a Professor in the Department of Materials Design and Innovation. The author or co-author of more than 90 research articles, he has been a principal investigator or co-investigator on approximately $15M of research and equipment awards.
An expert in mathematical modeling, for the last two decades he has been studying uncertainty quantification – techniques for understanding uncertainty in models of physical or biological systems, and how computing can account for these uncertainties.
Jasmina Tacheva is a Visiting Assistant Professor in the Department of Operations Management and Strategy at SUNY Buffalo’s School of Management.
Bridging quantitative, qualitative, and critical methodologies, particularly transnational feminist theories, her work investigates the intersection of data, technology, and societal impacts, and has been featured in journals such as Big Data & Society. Her most recent work is focused on a critical analysis of the complex ecosystem of AI technologies and their connection with the propagation of mis- and disinformation.
