AI and Race, w/ Dr. Broderick Turner and Angela Yi

In this episode of AI-Curious, we dive into one of the most complex and critical issues in AI development: the intersection of AI and race. Our guests, Dr. Broderick Turner, assistant professor of marketing at Virginia Tech, and Angela Yi, a doctoral candidate at Virginia Tech, share insights from their groundbreaking research on how race is represented in AI systems and the consequences of those representations.
Their paper, “Representations and Consequences of Race in AI Systems,” challenges us to ask: When should race be included in AI models? When should it be excluded? And how can we ensure that AI systems treat all human lives equally, without perpetuating harmful biases?
We discuss real-world examples of how racial biases in AI systems can lead to inequitable outcomes, particularly in fields like healthcare, policing, and facial recognition. Dr. Turner explains why treating race as a fixed category rooted in historical systems of oppression can result in unintended consequences, and Angela Yi offers a compelling framework for how developers can better approach race in AI.
From the TRAP Lab (Technology, Race, and Prejudice Lab) to practical ways companies can audit their AI models for fairness, this conversation is essential for anyone working in AI, tech, or policy. This is an episode you won’t want to miss if you’re serious about making AI more ethical and inclusive.
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