Generative AI Ethical Considerations and Discriminatory Biases on Diverse Students Within the Classroom

Abstract

Generative artificial intelligence (AI) can induce a variety of biases that can impact decision-making processes, and it can produce inaccurate or distorted information that may harm marginalized student groups in higher education classrooms. With the increase in generative AI use among college students and instructors, it is important to examine the ethical risks and discriminatory biases that can negatively influence students' learning experiences. For this purpose, this chapter focuses on the different types of generative AI ethical risks that can occur in U.S. classrooms. The variety of AI discriminatory biases against diverse student populations are also documented. Further, the authors discuss a case application that expands on the potential AI biases in higher education. To prevent and address potential AI ethical risks and biases, recommendations are offered to higher education educators. Lastly, guidance is offered suggesting future research in AI biases and diversity in higher education institutions.

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