AI for Equity: Unpacking Potential Human Bias in Decision Making in Higher Education

Abstract

The purpose of this study is to show how AI can serve as an assessment tool to detect potential human bias in decision making for students in higher education. Using student application data, we conduct a small study and apply a set of algorithms to perform deep learning analyses and assess human behaviors when identifying scholarship recipients. We conduct an interview with the organization’s leaders using this data to understand their criteria and expectations for identifying scholarship recipients and collectively explore the insights uncovered using these algorithms. Upon comparison to those recipients awarded the scholarships, we identify opportunities for the organization to implement a quantitative framework—a repeatable set of algorithms to help identify potential bias before awarding future scholarship recipients.