Edtech Equity
By Nidhi Hebbar and Madison Jacobs, with support from Matthew Volk and Elizabeth Allendorf
Black and Brown students in American public schools battle discrimination in many forms: higher rates of suspension, less advanced academic tracks, and a lack of cultural responsiveness from predominantly white teachers. Edtech products that use AI and machine learning can amplify already existing biases and introduce new ones. Education technologies promise to personalize learning, identify at-risk students, and automate administrative tasks for educators, but many do not take into account the unique challenges facing the Black and Brown students that make up over half of the American K-12 public school population. These policy briefs propose a Racial Equity Toolkit for AI in Edtech to enable companies and schools to uncover and mitigate racial bias at each stage of their product design and development, from ideation to implementation.
These briefs were completed as part of a project for the 2020 Aspen Tech Policy Hub Fellowship, a program designed to teach technology experts how to impact policy.
