Artificial intelligence (AI) systems are often presented as objective. But plenty of evidence shows that AI systems can reflect and reinforce existing inequalities, from healthcare and education to scientific research itself.

In the first seminar of our new research seminar series on applied AI , Thema Monroe-White from George Mason University explored how we can better understand — and challenge — these patterns. Her talk focused on race-conscious algorithmic approaches to AI and data, and what they reveal about how knowledge is produced, represented, and used.

Thema Monroe-White is Associate Professor of Artificial Intelligence and Innovation Policy at the Schar School of Policy and Government and the Department of Computer Science (joint) at George Mason University.

Drawing on two large-scale studies in her seminar, Thema showed that both scientific research and AI systems are shaped by human identities and social structures, and that recognising this is essential for educators, researchers, and anyone…