Artificial Intelligence (AI) is increasingly integrated into education through predictive analytics, adaptive learning, and behavioral monitoring. While AI is often presented as an objective tool for improving educational outcomes, its application can perpetuate systemic inequities. This paper explores the intersection of AI, race, and gender through a deeply personal narrative. Specifically, this paper recounts the experience of a college student and a professor who relied on an AI-driven plagiarism detection system to “prove” her work was not her own, implicitly suggesting that she lacked the intellectual capacity to succeed. While framed as a neutral technological judgment, the accusation reflected underlying racial and gender biases—signaling that being Black and female was equated with academic dishonesty and incompetence. This experience illustrates how algorithmic tools, when deployed without cultural awareness or critical oversight, can reinforce stereotypes and marginalize students of color that ultimately contribute to discriminatory outcomes. The author(s) conclude by proposing strategies for culturally responsive AI implementation, ethical safeguards, and policy interventions to ensure that technology serves as a mechanism for empowerment rather than exclusion. By centering lived experience, this work challenges the myth of AI neutrality and calls for urgent accountability in educational technology.

Authors:
Charmion Rush, Western Carolina University, United States
Jordyn Singletary, Western Carolina Univeristy, United States

About the Presenter(s)
Dr. Charmion B. Rush is an Associate Professor of Inclusive and Special Education at Western Carolina University. Dr. Rush earned her Ph.D. from the University of North Carolina at Greensboro in Special Education/Teacher Education and Development.

See this presentation on the full schedule – Thursday Schedule

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