To AI or not to AI? That is the question

Tell me if you agree. University educators should focus on developing their students’ foundational knowledge, universal skills like critical thinking, and personal characteristics like self-confidence. Right? I’m going to try to convince you that while accurate, this misses one of our key roles, and that AI has made this role even more important. I’ll also give you an exercise you can do with your students. 

I’m Dr Sarah Birrell Ivory, author of Oxford University Press’ Becoming a Critical Thinker and a recipient of a prestigious Aspen Institute Ideas Worth Teaching award. I now work with universities on issues like critical thinking and AI use. 

Recently, I heard a commentator point out that AI companies no longer talk about the benefits of AI to society, and instead they focus on what it can do. That is, they’ve forgotten about the translation piece, from what it can do to why it should be allowed or indeed encouraged to do those things. I’d like to equate that view to university education.

As university educators, I worry we spend too much time explaining to students what they need to do and not enough time convincing them of the benefit of being able to do those things. We’re missing that translation piece. And with student debt racking up and graduate employment drying up, students want to know why. Why go to university? And why learn the skills you’re offering? Especially when they perceive, they perceive, that AI offers a shortcut to the same outcome. 

So, the key role we need to embrace as university educators is being outspoken advocates for university education. We need to sing that from the rooftops. A university education makes you a better thinker. It changes how you approach tasks and problems. It offers you friction which you have to struggle through, and when you get to the other side, the confidence knowing you could do that.

Where AI enhances these benefits, fine; where it erodes these benefits by shortcutting the process, that is the problem. I don’t need to convince you of this. You know this. But I would like to offer you an exercise I call: to AI or not to AI? 

So, choose two topics, individuals or issues that hold some level of controversy in your field and preferably aren’t directly related. Students will need to answer three questions. What is the topic about? Why is it important in the context of your field? And why is it controversial? However, the first topic they can use only one or two written sources that you provide them. You might provide a book chapter or a level-appropriate article that they must read. For the other topic, they can only use AI.

This works best if all the work is done within the first half of a two-hour lecture, but the tasks I’ve explained so far can be set as homework, if necessary. 

Now, we come to the important part.

In the second half of the class or the next class, pair them up and ask them to explain their findings to their partner without relying on any notes. Then, as a reflection, ask which they learned the most about, which they remembered the most about, and which they were the most confident in discussing. 

Conclude by exploring the following four points. First, productive struggle. It was likely harder to work with the written text because students had to interpret the text, understand how it related to the questions and then construct their own answers. That is, they did the hard work that entered them into a state of “productive struggle”, as we talk about in my textbook. 

Second, understanding and recall. Because of point one, most students, if not all, will find this led to deeper understanding and better recall of the no-AI topic than the AI topic, even if the written answers for the AI topic were more comprehensive.

Three, process, not output. This demonstrates it’s not the output, “knowing the topic”, but the process, becoming a better thinker, that matters. With improved thinking skills, students can better examine information, knowledge and resources in the future, including AI answers. Without improved thinking, students may enter a state of cognitive surrender. 

And four, confidence during life’s turning points. Students will rely on better thinking and not AI outputs during key turning points in their lives: during a job interview when their answer doesn’t sound the same as every other candidate because they make an unexpected observation; when the person they’re chatting to at a networking event is impressed by their ideas and wants to talk again; when they’re faced with an unexpected question after a work presentation and they can quickly think laterally; at the end of an investor pitch, when a potential funder is reassured by their confidence in responding to left-field questions.

I’m Dr Sarah Ivory. Thank you for listening and I hope I’ve convinced you to embrace your role of advocate of university education and to try the exercise To AI or not to AI, so that we demonstrate to students the value of becoming a better thinker at university.

Sarah Birrell Ivory is a critical thinking advocate and educator. She is author of Becoming a Critical Thinker: For your University Studies and Beyond (Oxford University Press, 2021), Introduction to Management: Functions and Challenges, co-authored with Emma Macdonald (OUP, 2024) and Becoming a Critical Thinker on Substack.

If you would like advice and insight from academics and university staff delivered direct to your inbox each week, sign up for the Campus newsletter.