Leah HennigFrom cognitive atrophy to plagiarism, loss of human connection, and even just plain misinformation, professors should not be using artificial intelligence (AI) in our classrooms. More than that, the University of Alberta definitely shouldn’t be supporting them.
Picture this: you walk into your class for the first time this year. Your professor introduces the course, tells you a bit about themself, and then starts their lecture. The first thing you see is an image of Sigmund Freud talking to Charles Darwin in 4k definition. The notes that go along with the generated image are also clearly made by one of the many large-language models (LLMs) used by professors. What I want to know is how anyone takes that class seriously.
As I started my third year this fall, and I’ve noticed a massive upswing in the use of AI for teaching. It’s moved beyond the sphere of organization and management. Now, many professors use AI for the creation of images, presentations, assignments, and even actual course content. AI can be used effectively in many contexts, but teaching is not one of them.
One of many reasons why AI shouldn’t be used in lectures is because AI undermines the entire learning process. An instructor’s job isn’t to put information on a screen. Professors are supposed to explain difficult concepts, engage with students, and encourage people to think for themselves. Using AI to teach fundamentally opposes that role. A professor should model how to reason with a problem and deal with uncertainty; AI forgoes the entire intellectual process.
Another major concern is the issue of accountability and intellectual property. AI is known for producing convincing but often inaccurate content. LLMs, specifically, will fabricate references and create misleading conclusions. While AI is becoming increasingly capable, it doesn’t have to be wrong all the time to be a problem; even occasional errors can have serious consequences. Any amount of misinformation is too much, especially in university. Even worse, AI will get to a point where students cannot easily recognize its mistakes.
The U of A’s own AI framework states that users are responsible for the outputs they generate and must fact-check and verify their accuracy. If the university already recognizes that responsibility, then professors should be held to the same standard when using AI to create teaching materials. AI should not become an excuse for misinformation in the classroom.
One of the most glaringly obvious issues is the clear double standard between students and instructors. Students will face academic misconduct accusations and investigations if they are suspected of AI use; meanwhile, professors can use AI to their heart’s content. It is important to note that the U of A’s policy emphasizes accountability, transparency, and human oversight. However, there isn’t clear oversight regarding the use of AI. Many professors use models for grading and creating work without explicitly telling students. We have to recognize that the use of AI by students and instructors is not always equivalent. However, both should be governed by fair and clear policies.
The use of AI in universities has been a topic of conversation over the last few years; however, it has specifically focused on the student side of learning. The majority of the focus has been on academic misconduct, plagiarism, and discipline. If universities expect students to think critically, produce original thought, and be responsible for what they submit, then professors should be held to those same standards. Students cannot be expected to value the learning process if professors are willing to outsource it. If we allow AI to take over the process of teaching, we will lose everything that makes higher education valuable and worthwhile.
