[Exclusive] Only 37% of national and public universities have AI guidelines; professors and students say "no help"

On September 8-21, a nationwide survey of 52 national and public universities revealed that only 19 (36.5%) of them have established artificial intelligence (AI) usage and ethics guidelines. At the University of Pusan, Seoul National University, and others, only basic principles such as AI as a learning assistance tool and individual responsibility for final accountability are mentioned.

This lack of specificity has caused confusion among students regarding acceptable usage and penalties, leading to unnecessary suspicion when students claim to have received AI assistance.

For instance, 23-year-old Han Yeon of the Korean Literature Department at Gyeongju National University expressed her frustration, stating that the university's guidelines only contain generic statements without specific usage rules, which do not help in addressing the issue. Despite the proliferation of AI-powered devices across college campuses, many institutions lack concrete guidelines, leaving teachers and students with only declaration statements and lacking practical effectiveness.

In response to this gap, some universities are taking matters into their own hands. Seoul National University's Department of Computer Science has drafted a guideline with four stages of AI usage based on the specific nature of each field of study. They have already flagged AI-assisted assignments as fraudulent during the past semester.

Professor Park Gyeong-su from the Department of Computer Science at Seoul National University noted that a one-size-fits-all approach may not be effective due to the unique characteristics of various disciplines, hence the need for separate guidelines.

International universities are also grappling with the implications of AI on higher education. Massachusetts Institute of Technology (MIT) recently released a report by its AI usage and ethics temporary committee, which recommended that faculty determine the learning objectives for each course and then decide on the appropriate use of AI based on those objectives.

This includes shifting from AI-generated detection tools to in-person supervision, step-by-step feedback, and addressing the disparity between pay-for-use and free AI users.