The integration of artificial intelligence (AI) into the academic sphere is sparking a debate among educators worldwide. With AI-powered tools like large-language models becoming increasingly popular, universities are grappling with the ethical implications and practical challenges of integrating these tools into their curriculums.

While some educators see AI as a powerful tool for research and learning, others express concerns about its potential to undermine the learning process and facilitate academic dishonesty. The AI debate in academia is essentially a discussion between two contrasting views: one that embraces AI as an inevitable part of academic progression, and another that views it with caution and skepticism.

Ajay Parasram, a professor at a prominent Canadian university, argues that AI can simplify the process of discovery but can also exclude crucial information due to its inherent biases.

According to Parasram, the restricted search results to peer-reviewed articles and leading journals reinforce certain intellectual discourses. He worries that students are rushing to find the right answer instead of enjoying the process of intellectual discovery. Advocating for students to take control of their own learning and exercise critical thinking, Parasram advises against the use of AI in research, arguing that it undermines their learning experience.

On the other hand, Sharon Lauricella, a professor at Ontario Tech University, encourages her students to use large-language models. Lauricella likens these AI tools to a chainsaw – they can be useful if handled correctly.

She teaches her students to question the information AI might not be showing them and how to rephrase questions to get the desired answers. Lauricella also encourages the use of AI to summarise information, help form ideas, and check grammar, which she refers to as the bookends of a research project.

However, Lauricella agrees with Parasram that AI is not designed to provide credible research and that critical thinking remains essential for students. She allows her students to use AI for background research, but insists their work should be unique and reflective. If students use AI, she requires them to disclose its use and credit it in their assignments.