This rebuttal was written by Gen AI, specifically, a Boodle Box bot (a.k.a. custom GPT) called Logic Architect. I thought it was fun to have the Gen AI craft a response, but I admit, it did a thorough analysis. However, for the sake of length, I have made some cuts and edits.

While some may say, “I’m not reading the rebuttal,” if you think about it, in some ways, it proves Cutler’s point. I doubt that I would have had the time and stamina to review, break his arguments down into premises, find the gaps and/or fallacies in his logic, then construct a rebuttal. But that is what the Logic Architect was able to do. I also had another bot, Outline Helper, make an outline. If I was doing this for class, I would have done the work. Since I’m not, my goal was really to see if Cutler’s post and Facebook clarification post held up under logical scrutiny. His original post did, but the Facebook post, perhaps, not so much. But it’s Facebook, right?

All that aside, this was simply an experiment. I often apply Logic Architect bot to my own writing and thinking in the hopes of getting to a better point. The most recent time I did it, I had an insight I hadn’t had before. We often have a bunch of “premises” but we’re not sure how to group them to make an argument. We group them into premises to make an argument, but then we realize something is missing. At that point, you can ask Logic Architect, “Hey, my meatsack brain is leaving stuff out. What am I missing?” I write that down, then repeat this process again and again, until I internalize it. For me, that’s the benefit. It’s like having a tutor/mentor who can answer my questions when I need someone to do that.

Introduction

In his thought-provoking article “ChatGPT-5 Just Changed My Mind — AI Has No Place in My Classroom,” educator David Cutler presents a compelling case against the use of generative AI in educational settings. While his concerns about student intellectual development deserve serious consideration, this rebuttal argues that a more nuanced approach to AI integration better serves our educational goals.

Rather than viewing AI as either a complete replacement for thinking or merely a marginal tool, we should explore the rich middle ground where AI becomes a pedagogical partner in developing critical thinking skills. This position paper examines the logical inconsistencies in Cutler’s arguments while proposing a balanced framework for AI integration that enhances rather than diminishes student learning.

The False Dichotomy of AI Use in Education

Cutler’s position establishes a false dichotomy between complete AI prohibition and unrestricted use. In his original article, he states, “When a free or inexpensive tool can fully replace the thinking process, it stops being a support and becomes a substitute brain.” This framing ignores the spectrum of integration possibilities between these extremes.

Educational research consistently demonstrates that tools exist on a continuum of implementation, not as binary choices. As Mishra and Koehler’s TPACK framework illustrates, effective technology integration requires thoughtful consideration of how tools interact with content knowledge and pedagogical approaches.

Furthermore, Cutler’s clarification that he uses AI for “narrow, practical ways” like feedback and transcription while drawing “the line at content generation” reinforces this dichotomous thinking. This position fails to acknowledge how content generation tools, when properly integrated into curriculum, can serve as thought partners rather than thought replacements. The either/or framing ignores the rich middle ground where AI becomes a collaborative tool in developing critical thinking.

The Flawed Muscle-Building Metaphor

Central to Cutler’s argument is the muscle-building metaphor: “Muscles only grow under load. Nobody ever got stronger by watching someone else work out.” While intuitively appealing, this analogy breaks down under scrutiny. Effective physical training rarely relies on unassisted struggle alone; rather, it incorporates specialized equipment, coaching, and progressive resistance tailored to individual development.

Educational research from Vygotsky’s Zone of Proximal Development to modern scaffolding theory demonstrates that learning thrives not through unassisted struggle but through appropriately challenging tasks with strategic support. AI can provide this adaptive scaffolding, offering different levels of assistance based on student needs and gradually reducing support as competence develops. Just as a weight machine provides appropriate resistance while guiding proper form, well-implemented AI can offer the right level of challenge while modeling effective thinking processes.

Rather than preventing growth, properly implemented AI scaffolding enhances intellectual development by providing the right level of challenge and support, similar to how training tools and coaches enhance physical development.

The Pedagogical Opportunity of AI Integration

Cutler’s approach focuses primarily on preventing AI misuse rather than teaching responsible AI use. He writes, “I want to limit student access to content-generating AI for as long as possible. Build fundamentals first, then open the toolbox.” This restriction-first approach overlooks a crucial educational responsibility: preparing students for the technological realities they will face throughout their academic and professional lives.

AI tools will be ubiquitous in students’ futures. According to recent workforce projections, over 80% of professional roles will involve AI interaction by 2030. Educational responsibility includes equipping students with the critical evaluation skills necessary to navigate this landscape. Teaching students to critically evaluate AI outputs—identifying strengths, weaknesses, biases, and limitations—develops higher-order thinking skills that transfer across domains.

Rather than restricting AI access, educators should embrace the opportunity to teach critical AI literacy, helping students develop the metacognitive skills to evaluate, refine, and responsibly use AI-generated content. This approach transforms AI from a potential threat into a powerful teaching tool for developing discernment and judgment.

The Historical Pattern of Technological Integration

Cutler dismisses the calculator comparison, claiming AI is fundamentally different: “Calculators could produce a numerical answer, but only after the student decided which problem to solve and how to set it up; calculators didn’t generate ideas, craft arguments, or interpret meaning.” This perspective overlooks the historical pattern of technological integration in education.

Every major educational technology—from books to calculators to the internet—initially faced resistance based on fears of cognitive outsourcing. Socrates worried that writing would weaken memory; educators feared calculators would undermine mathematical understanding; internet access raised concerns about research skills. Each technology was eventually integrated through thoughtful pedagogical adaptation that preserved core learning objectives while leveraging new capabilities.

The consistent pattern of initial resistance followed by thoughtful adaptation suggests that AI, like previous educational technologies, will find its appropriate place in education through integration rather than restriction. Historical perspective reminds us that educational practices evolve alongside technological capabilities, often in ways that expand rather than diminish learning opportunities.

The Misalignment of Restrictive Policies with Educational Goals

Cutler proposes restricting AI use to in-class, monitored environments: “Every substantial piece of writing will happen in class, either in old-school blue books or on Digiexam—a secure, locked-down digital platform that lets me monitor work in real time.” While well-intentioned, this approach creates a fundamental misalignment between policy and educational goals.

The stated goal is developing students’ independent thinking abilities, yet real-world thinking increasingly requires evaluating and integrating multiple information sources, including AI-generated content. By restricting AI access, students lose the opportunity to develop critical evaluation skills for AI outputs—precisely the skills they will need in their academic and professional futures.

This means-end inconsistency undermines the policy’s effectiveness. If we aim to develop independent critical thinkers prepared for a world where AI is ubiquitous, students need guided practice evaluating AI-generated content, not protection from it. Policies that restrict AI access are misaligned with the goal of developing thinkers prepared for a world where AI requires thoughtful evaluation.

Conclusion

The debate around AI in education need not be framed as a binary choice between unrestricted use and prohibition. David Cutler’s concerns about AI replacing student thinking are valid but lead to an unnecessarily restrictive approach that misses valuable pedagogical opportunities.

A more balanced perspective recognizes AI as a potential pedagogical partner that can enhance rather than replace critical thinking when properly integrated into curriculum.

Like effective physical training that uses equipment and coaching, intellectual development benefits from appropriate scaffolding that AI can provide. Students will encounter AI throughout their lives; education should prepare them to use it responsibly rather than shield them from it.

The integration pattern of previous educational technologies suggests AI will find its appropriate place through adaptation rather than restriction. Teaching students to critically evaluate AI outputs develops higher-order thinking skills that are increasingly essential in an AI-rich world.

Rather than banning content-generating AI, educators should consider teaching AI literacy alongside traditional writing skills, designing assignments that incorporate AI as a drafting partner while requiring critical evaluation, developing assessment methods that value the process of refining AI outputs, and creating opportunities for students to compare their independent thinking with AI-generated content.

This approach acknowledges the legitimate concerns about intellectual development while preparing students for the technological reality they will navigate throughout their lives. By embracing AI as a pedagogical partner rather than an adversary, we can fulfill our educational mission more effectively in a rapidly evolving technological landscape.