Exploring ethical concerns and affordances of generative AI in higher education: Perspectives of underserved students

Abstract

The study explores the ethical concerns and the affordances of generative artificial intelligence (GenAI) in higher education from the perspectives of underserved students. Data were collected through a survey of 77 students in a public university with predominantly underserved students in the United States. Informed by the five principles of AI ethics and technology affordance theory, the study employed a mixed-methods approach. Qualitative analysis of the narrative data revealed six themes: utility affordances, value affordances, user behavior, AI use outcomes, the contingency of ethical AI use, and a pessimistic view of ethical AI use, suggesting that ethical considerations in GenAI use depended on user perspectives. Furthermore, quantitative analysis indicated that student perceptions of the ethical use of GenAI varied by their demographic and socioeconomic background. The study also revealed nuances of the digital divide in AI. The study contributes to the literature by proposing an integrated model of ethical GenAI use and offers practical implications for promoting effective and ethical use of GenAI in higher education.