  I investigate bias in terms of ChatGPT's college major recommendations for
students with various profiles, looking at demographic disparities in factors
such as race, gender, and socioeconomic status, as well as educational
disparities such as score percentiles. By constructing prompts for the ChatGPT
API, allowing the model to recommend majors based on high school student
profiles, I evaluate bias using various metrics, including the Jaccard
Coefficient, Wasserstein Metric, and STEM Disparity Score. The results of this
study reveal a significant disparity in the set of recommended college majors,
irrespective of the bias metric applied.
