In what ways is educational AI biased?

This season Libby Hills from the Jacobs Foundation and AI researcher Owen Henkel continue to speak with leading researchers, practitioners and educators on the Ed-Technical podcast series about the cutting edge of AI in education. They will break down complex AI concepts into non-technical insights to better understand what the research says and help educators sift the useful insights from the AI hype. 

This episode, Owen and Libby speak to Ryan Baker, a leading expert in using big data to study  learners and learning interactions with educational software. Ryan is a Professor in the Graduate School of Education at the University of Pennsylvania, and is Director of the Penn Center for Learning Analytics.

Ryan provides an overview of educational data mining (otherwise known as EDM) and explains how insights from EDM can help improve learner engagement and outcomes. Libby and Owen also explore the technical aspects of algorithmic bias with Ryan, discussing why it matters, how it is defined, and how it can be addressed from a technical perspective. 

Links

Ryan Baker biography 
One of Ryan Baker’s research papers about algorithmic bias 
Big Data and Education – Ryan Baker’s free massive online open textbook