Resisting AI's Cognitive Offload with Leon Furze

A few weeks ago, I interviewed author and consultant Leon Furze for Intentional Teaching. You may know Leon from his work on the AI Assessment Scale or his series of articles on teaching AI ethics. I've been citing his work for a while now, and I was eager to talk to him about several of his recent blog posts, especially this one and this one on ways we can support student use (and non-use) of AI to resist cognitive offloading.

During our conversation, Leon got me thinking about the mental models that we (educators and students) have of working with AI, so much so that I was compelled to write a 1700-word blog post to get some of my thoughts down on paper! I published that post on May 15th, over two weeks before posting my interview with Leon to the podcast feed earlier this week. Y'all got to read some of my thoughts about that interview before actually hearing the interview itself! Time isn't always linear when you're a podcaster.

I've said for a few years now that expert AI use requires expertise. That's a problem for education, since our students are using AI before they've developed that expertise. How can we help our students approach AI in ways that encourage the development of expertise--and avoid the cognitive offloading that AI offers? Leon has a really useful take on that question. Drawing on the metaphor of resistance in strength training, he shares a framework in our conversation for the kinds of expertise that students need to use AI well. We also talk about those mental models of AI I mentioned above--that's what inspired me to write that blog post.

Leon is such a deep thinker about AI and education, and his work is informed by research and by his work with educators in Australia (where he lives) and elsewhere. (When we spoke, he was a day ahead of me thanks to time zones. Again, time is a little wonky for podcasters.) I hope you'll take time to listen to our conversation!

​You can listen to my interview with Leon Furze here, or search "Intentional Teaching" in your podcast app. And if you do search your podcast app, would you click that follow button while you're there? I've a lot more fascinating interviews already recorded that I'm excited to share on the podcast this summer.

AI-Aware Teaching on Tea for Teaching

I've been a fan of the Tea for Teaching podcast hosted by John Kane and Rebecca Mushtare for years. I don't know when I started listening, but they started podcasting in 2017, and I'm pretty sure I was an early listener. John and Rebecca feature "guests doing important research and advocacy work to make higher education more inclusive and supportive of all learners." They do a great job selecting guests and spotlighting the teaching wisdom their guests have to share.

This week on Tea for Teaching, those guests are my Norton Guide to AI-Aware Teaching co-authors Annette Vee and Marc Watkins and me. This was actually the first podcast interview the three of us did, although since it was recorded we did a live podcast recording with Eric Mazur for his Social Learning Amplified podcast. (Again, timelines are weird in podcasting land.) We talk about the origin of the book, during which Annette compares us to a boy band, and I reveal to my co-authors that I wasn't sure I would enjoy co-authoring a book when I signed on!

We cover a lot of ground in the interview, providing a nice introduction to the book along the way. John and Rebecca ask the hard questions, like how educator can assess student learning when students can offload the work to AI, what open there is for online learning in an age of AI, and how we should be updating our learning goals to account for AI's growing use in the workplace. I enjoyed sharing some wisdom that Annette, Marc, and I gained while writing the book, and really enjoyed hearing my co-authors' perspectives on these hard questions.

One observation that occurred to me during the interview: I came on the book project as the more AI-forward member of the writing team, with lots of ideas about how faculty can use AI to create new learning experiences for students. Annette and Marc were more cautious about AI, especially because of the anti-AI sentiment in their world of writing instruction. Somehow, however, by the end of the writing process, some of that dynamic had flipped. I'm more interested in ways to teach students to "think without machines" (as the president of the University of Chicago phrased it earlier this week), and Annette was the one in the Tea for Teaching interview sharing the cool things she and her University of Pittsburgh colleagues are doing with AI these days!

Thanks to John and Rebecca for having us on and for asking such good questions! You can listen to our AI-aware teaching interview here, or search for "Tea for Teaching" in your podcast app.