Is It Ethical for Teachers to Use AI for Student Feedback?

Abstract

Providing feedback to students is an important yet time-consuming part of teachers’ work. Advances in AI technologies, especially generative AI, have introduced innovative solutions to automate the feedback process. The use of AI for feedback has generated interest in higher education, mainly attributed to its potential to reduce teachers’ workload and enhance feedback timeliness in response to the massification of university education. However, there remains a gap in empirical research that focuses on the ethical implications of this practice. In view of this, the paper draws on a diverse dataset (i.e., university policy reviews, social media posts and interviews with university teachers and students) to extrapolate eight key areas of ethical considerations regarding teachers’ use of AI for feedback purposes. Building on these areas, we call for a more nuanced understanding of what it means for teachers to use AI for feedback, considering various contextual complexities such as the purposes of assessment, the features of student assignments, and the types of feedback automated by AI. The study also highlights the need to move beyond the binary question of whether teachers should use AI or not towards exploring how feedback activities and teacher AI use could be designed and operated in ways that maintain and even enhance care, trust, and human connections central to effective feedback processes. While the study focuses on teachers, promoting the ethical use of AI requires a collective effort from multiple stakeholders in and beyond higher education.