AI ethics in academia among higher education students’ perceptions and practices

Abstract

AI ethics has become an essential part of higher education today, reshaping traditional ideas about academic honesty for the digital age. It remains unclear how students interpret the ethics of AI use, experience ethical principles, and apply guidelines in their academic settings. To fill the gap, this study explores perceptions and practices of AI ethics among higher education students at Banaras Hindu University (BHU), using the AI and Ethics Perception Scale (AEPS) dimensions, including transparency, accountability, privacy, fairness, and human oversight, as a conceptual framework. An interpretative qualitative case study was conducted with 15 purposively selected students from seven departments at BHU. We analysed responses from their semi-structured interviews using thematic analysis. The study findings show that most students (N = 10) perceive AI as lacking transparency, particularly regarding its sources and accuracy, and acknowledge their accountability for AI-assisted work. Students (N = 15) expressed concern about privacy, particularly about avoiding the entry of personal, financial, or academic information into AI systems. The study also found that teacher review plays an important role in maintaining academic integrity. Students reported frequent use of AI in their own educational tasks, often without considering ethical implications. The use of AI has affected their study habits, time management, and learning strategies, while also reducing their stress levels. This study suggests that universities should develop their own ethical guidelines and frameworks for the use of AI. They should also conduct seminars and workshops to raise awareness among students and teachers about ethical AI use in academia.