Three years ago, asking a website to write your essay sounded like science fiction. Today, it takes 15 seconds and an email account. As tools like ChatGPT and Google Gemini become fixtures of student life — Notre Dame students 18 and older can access Gemini and Google NotebookLM through their university accounts — professors are now, more than ever, rethinking how assignments should be built, how integrity will be protected and how the Honor Code will be applied to a technology that evolves by the day.
The most visible change due to this advancement is in the assignments themselves. Work that once could be completed entirely online is increasingly moving back to paper, with some professors now requiring students to handwrite at least part of what they submit for grading. Alongside that shift, faculty now lean harder on detection software. Particularly, plagiarism and AI-checking tools like Turnitin are now routinely used to screen student work as it comes in, creating a kind of arms race between the tools students might misuse and the ones instructors use to catch that misuse. Other adaptations add to the picture, as more in-class and oral exercises emerge, all serving as a deterrent for this inappropriate technology use. Many students are aware of this reality; when asked about her thoughts on AI usage in the classroom, a Notre Dame sophomore said, “AI can be beneficial to a point. There’s a line that you can cross, and once you cross that line, then you’re hurting yourself more than you’re helping yourself.”
Yet, faculty are candid about a hard truth: There is no foolproof way to guarantee a student won’t use AI. Handwriting work and detection software lower the odds, but they can’t eliminate them. Because of that, many professors turn from policing to persuasion. During syllabus week especially, many instructors will make a pointed case against leaning on AI for the wrong tasks. Specifically, using a chatbot to grind through calculus homework or to complete online assignments for a language class, they argue, offers no real learning benefit — it simply outsources the practice that is needed to succeed. They will further argue that the consequences will show up later — in person. If a student were to entirely rely on AI for daily work going into a closed-book setting like midterms, they are practically setting themselves up for failure. Framed this way, professors make a convincing case that integrity when it comes to AI becomes a matter of self-interest as much as abiding by the rules.
This doesn’t mean that professors don’t realize that AI can be a helpful tool in the classroom, however. A Notre Dame professor believes that AI “can be a helpful study guide tool for students only if it doesn’t replace their learning.” With AI’s ability to explain difficult concepts, consolidate study terms into a study guide and create practice questions, the extent to which the technology is utilized ultimately determines what students get out of it. It’s difficult for students to put these boundaries into practice, however, meaning that AI’s benefits might come to pass only in theory.
The importance of not replacing your work and learning with AI ultimately rests on a foundation older than any AI tools. At the beginning of every year, Notre Dame students sign the Honor Code pledge, taking on the responsibility to abide by principles of intellectual integrity and thereby promising not to participate in or tolerate academic dishonesty. The code was written long before generative AI, but its core principle — never representing others’ work as your own — extends to this technology almost seamlessly.
The University of Notre Dame made that extension explicit in its August 2023 Generative AI Policy for Students, which states plainly that “representing work that you did not produce as your own, including work generated or materially modified by AI, constitutes academic dishonesty.” Crucially, the standard is instructor-centered, meaning that when a violation occurs to an instructor’s articulated policy or used it to complete coursework in a way not expressly permitted by the faculty member, it will be considered a violation of the Honor Code. Hence, this is why the rules and standards of whether generative AI is permitted in classrooms differ from one professor to another.
As these tools become increasingly more common, the burden shifts toward clear communication and student integrity, as both sides work together to create a studious environment that ensures fairness and prestige standards. The university’s own framing captures the goal best: AI should supplement a student’s education, not replace it.