Artificial Intelligence in Higher Education: Student Knowledge, Attitudes, and Ethical Perceptions in the United States

Purpose: This study examines undergraduate college students’ knowledge, attitudes, and behaviors regarding artificial intelligence (AI), with a particular focus on its use in classroom, coursework, and personal applications. The objective is to provide empirical insights into how students perceive the benefits, risks, and ethical implications of AI adoption in higher education. Methodology: A cross-sectional survey was conducted among 319 students enrolled in a personal wellness elective course in the United States, of whom 258 (81%) completed the questionnaire. Data collection focused on familiarity with AI, frequency and context of use, perceived benefits, ethical concerns, and trust in AI systems. Statistical analyses included chi-square tests, Fisher’s exact tests, and ANOVA to examine associations between frequency of AI use and student perceptions. Findings: More than half of the students reported familiarity with AI, most frequently learning about it through the internet. Frequent AI users expressed higher levels of trust in AI, were more likely to believe that AI makes learning easier, and associated it with improvements in writing, critical thinking, and communication skills. In contrast, infrequent users were more likely to perceive AI use in class as cheating, express distrust in AI safety, and emphasize the need for stricter regulation. Overall, results highlight a “digital divide” between frequent and infrequent users, with implications for teaching practices and institutional policies. Originality/Contribution: This study contributes to the emerging literature on AI in higher education by offering one of the few empirical analyses of U.S. college students’ perspectives. It advances understanding of the ethical and pedagogical challenges posed by AI integration and provides evidence that can inform the design of institutional policies, curricula, and training programs. Practical Implications: The findings underscore the urgent need for universities to develop clear policies and training programs on the responsible use of AI. Institutions should promote AI literacy among both students and faculty to address ethical concerns, reduce academic integrity risks, and prepare students for future workforce demands shaped by technological innovation. Limitations: The study is limited by its cross-sectional design, single-institution sampling frame, and reliance on self-reported data. Future research should expand to multiple universities, adopt longitudinal designs, and explore the perspectives of both students and faculty in greater depth. Alignment with the SDGs: This research contributes to the advancement of the United Nations’ Sustainable Development Goals, particularly SDG 4 (Quality Education), by addressing the role of AI in shaping educational practices, and SDG 9 (Industry, Innovation, and Infrastructure), by analyzing how emerging technologies influence higher education. It also supports SDG 16 (Peace, Justice, and Strong Institutions) by engaging with ethical and regulatory considerations surrounding AI governance in educational contexts.