What is the problem to which cognitive outsourcing is the solution?

A pilot study of philosophy undergraduates found that 79.1% of students recognized the importance of assigned readings but cited limited time (65.7%) and intellectual difficulty (33.3%) as barriers, with 76.2% expressing positive sentiment toward generative AI tools for making challenging content more accessible. The research suggests that while AI reading tools may help lower anxiety and democratize access to complex material, over-reliance on AI summaries risks impeding the development of critical reading and interpretive skills essential to philosophical education. The findings raise a diagnostic question for educators: what underlying problems in teaching and learning is cognitive outsourcing solving for students, and how can disciplinary expertise distinguish between undesirable obstacles and constitutive challenges that students must work through to learn?

This paper by Thomas Corbin et al https://learningletters.org/index.php/learn/article/view/35 reports on a pilot study of philosophy undergraduates exploring their use of AI-reading tools. Their analysis of half of students using generative AI tools in some way for reading. Interestingly, the vast majority 79.1% recognised the importance of this reading while also citing limited time 65.7% and intellectually difficulty 33.3% with the texts. They suggest a positive trend underlying the familiar fears about cognitive outsourcing. From pg 6: The strong positive sentiment toward GenAI availability 76.2% suggests these tools are making students more comfortable with challenging content, potentially lowering anxiety barriers to engagement with complex reading material. By providing alternative entry points to challenging texts, GenAI tools may help democratise access, particularly for students who face epistemic barriers to traditional engagement with reading materials. However, this optimistic interpretation must be balanced against potential risks. While GenAI may help students overcome initial barriers, over-reliance on AI-generated summaries could potentially impede the development of critical reading and interpretive skills that are essential to philosophical education. This is what I mean about the need to respond diagnostically to student AI use. There are real problems in teaching and learning being surfaced by developing trends in student AI-use. What is the problem to which cognitive outsourcing is the solution for students? In asking this question it becomes possible to diagnose the underlying challenges which pre-existed generative AI, as well as to better understand student use in a manner which enables us to steer them towards active rather than passive use of AI. This is a way of approaching student practice which enables us to surface difficulties . It still leaves us with the question though of which difficulties are undesirable obstacles and which difficulties are constitutive challenge . What do students need to work through in order to learn and how do we help them with this? versus what aspects of teaching and learning get in the way and should potentially be dispensed with? Is this part of the solution to s my overarching question https://markcarrigan.net/2026/05/26/what-does-it-mean-for-students-to-use-ai-in-active-rather-than-passive-ways/ of what it means for students to use AI in active rather than passive ways? Who can authoritatively judge whether a difficult falls is undesirable or constitutive ? I think it has to be disciplinary-based expertise. If you don’t keep the link with disciplinary expertise then you can’t solve the problems of generative AI. That at least is the conclusion I’m rapidly coming to, which I’ll explore in future posts in this series.