The comparison of artificial intelligence to calculators has become a popular refrain among advocates, administrators and policymakers seeking to justify AI integration in corporate and educational settings. This analogy, while superficially appealing, fundamentally misrepresents both the nature of AI and its impact on human cognitive development. The consequences of this misunderstanding are not merely theoretical, they are playing out in real classrooms with measurable effects on learning and intellectual capacity.

The reality of these stakes was starkly illustrated at UCLA’s 2025 graduation ceremony, when computational biology major Andre Mai proudly displayed ChatGPT-generated text on the jumbotron, showing fellow graduates and families the AI-produced work that helped him complete his final exams. As Mai scrolled through walls of AI-generated content while the crowd cheered, the moment crystallized a troubling trend: with 86% of students now using AI in their studies and 56% having used AI on assignments or exams, what was once considered academic dishonesty has become normalized, even celebrated.

The Lacking Equivalence

When people argue that AI is simply another tool like a calculator, they reveal a profound misunderstanding of how these technologies operate and what they demand from users. A calculator requires its user to possess substantial prerequisite knowledge: understanding of mathematical concepts, recognition of appropriate operations, knowledge of order of operations, variables, logical sequence of numbers, and the ability to interpret results within context.

The calculator amplifies human mathematical reasoning; it does not replace it. Remove the student’s understanding of math, and the calculator becomes useless.

AI operates under entirely different principles. As educational researcher Stephen Jackson observes, “It might be more helpful to imagine handheld calculators that routinely produced false results like 2+2=5” due to AI’s ability to “hallucinate,” or report false information. Unlike calculators, which perform deterministic mathematical operations, AI systems generate responses through pattern matching from training data, often producing plausible-sounding but incorrect information.

A student can input a complete assignment prompt into an AI system and receive a fully formed response without understanding the subject matter, the assignment requirements, or even the quality of the output. They do not need to comprehend basic grammar such as nouns, verbs, adjectives, adverbs, or understand sentence structure, paragraph organization, thesis development, or evidence evaluation. Traditional writing requires students to understand the building blocks of language and communication. With AI, students bypass not only these fundamental language skills but also higher-order processes. The AI performs not just the mechanical work, but the intellectual work as well.

The calculator fills a computational gap; AI fills a cognitive gap. The former supports learning; the latter can replace it entirely.

The Knowledge Void and Cognitive Offloading

This fundamental difference creates what can be termed a “knowledge void,” a space where learning should occur but doesn’t. Traditional educational tools require students to bring knowledge to the task. AI tools can function effectively even when students bring nothing but the ability to copy and paste.

Recent research provides compelling evidence for this concern. A 2024 study of 666 participants found a “significant negative correlation between frequent AI tool usage and critical thinking abilities (r = −0.68), mediated by increased cognitive offloading,” (Gerlich, 2025). This research demonstrates that as students increasingly delegate cognitive tasks to AI, their capacity for independent analysis diminishes.

These findings are reinforced by groundbreaking neuroscience research by MIT published in 2025, which used electroencephalography (EEG) to measure brain activity during essay writing tasks. The study revealed that “brain connectivity systematically scaled down with the amount of external support: the Brain-only group exhibited the strongest, widest-ranging networks, while LLM assistance elicited the weakest overall coupling.” Participants who relied on ChatGPT showed measurably weaker neural connectivity patterns, indicating reduced cognitive engagement during the learning process.

As documented across multiple studies, over time, overreliance on generative AI tools for academic tasks, instead of critical thinking and mental exertion, may damage memory retention, cognitive functioning, and critical thinking abilities. This represents a fundamental departure from calculator use, where the cognitive demands of problem-solving remain with the user.

Educational Destruction Through Effortless Achievement

Unlike previous educational technologies that required some level of engagement, AI can deliver sophisticated-appearing results with minimal input. This creates a dangerous feedback loop where students receive positive reinforcement for work they did not perform. When students discover they can obtain good grades without engaging in the learning process, the incentive structure of education breaks down.

Current data reveals the scope of this challenge: while 54% of students say using AI on schoolwork counts as cheating or plagiarism, they continue to use it extensively. Nearly half of students (48.2%) expressed concerns about the accuracy of AI-generated content, while over 50% believe over-reliance on AI will negatively impact their academic performance. These statistics reveal that students themselves recognize the risks, yet usage continues to climb. Additionally, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.

Over-reliance on AI algorithms results in complacency, which is particularly detrimental to critical thinking abilities. This erosion affects not just individual assignments but entire courses and subjects. Students who become accustomed to AI assistance lose tolerance for the productive struggle that characterizes genuine learning.

Evidence from the Classroom

My direct experience teaching approximately 1,800 students over nearly a decade (2016-2025) provides compelling evidence of AI’s disruptive effects. As an educator who has tracked both AI usage patterns and academic performance across this substantial student population, I have observed a clear and troubling correlation: as AI use goes up, grades go down, and students demonstrate increasingly poor mastery of course material.

The data from my classrooms tells a stark story. From 2016 to 2021, when AI usage remained minimal (1-2% of students), average class performance held steady at 3.84-3.87 GPA. However, beginning in 2022 with ChatGPT’s release, I observed a dramatic shift. As AI usage jumped to 5% of students, average GPA dropped to 3.75. By 2023, with 25% of students regularly using AI, average performance fell to 3.5. In 2024, with 60% of my students reporting AI use for assignments, average GPA plummeted to 3.25, nearly a full letter grade below pre-AI levels.

Even more revealing is the performance gap between AI users and non-users on in-person assessments. Students who self-reported heavy AI use for assignments scored an average of 1.3 points lower (on a 4.0 scale) on exams and oral presentations compared to students who completed work independently. In my 2024 classes, 78% of students who failed midterm exams had submitted AI-assisted homework that earned B+ grades or higher.

The pattern became clear by 2022 and 2023. Students who used AI heavily for assignments often struggled on tests and tasks where AI was not allowed. Research supports this, showing that real learning happens through active thinking and engagement. When AI does the thinking, students miss that process and end up with only a surface-level understanding.

This creates a false sense of success. The work looks good, but the learning isn’t happening. Simply put, no one learns when AI does the work for them.

Even more concerning is how this habit carries over. Students who rely on AI often struggle in live discussions, oral presentations, and timed exams. Their core skills weaken from lack of use, even though their submitted work still looks polished. In some cases, this shows up in job interviews, where candidates quietly use AI tools to answer questions they don’t understand, exposing a gap between what they appear to know and what they actually do.

The Broader Educational Impact

The impact of AI extends beyond courses explicitly focused on technology. English literature classes suffer when students use AI to analyze texts they have not carefully read. History courses become meaningless when students submit AI-generated research papers on topics they have not investigated or that outputs biased perspectives from the AI’s training. Mathematics instruction fails when students use AI to solve problems they cannot understand.

Current usage statistics reveal the scope of this challenge. Ohio State University announced in June 2025 that all students will be required to train in artificial intelligence, with the goal of making every graduate “fluent in AI and how it can be responsibly applied to advance their field.” However, the approach reveals the fundamental tension at the heart of the calculator analogy: while the university prohibits students from using AI to “pass off assignments as their own work,” it simultaneously encourages AI integration across the curriculum.

This contradiction highlights the challenge facing educational institutions. As Associate Professor Steven Brown noted, “It would be a disaster for our students to have no idea how to effectively use one of the most powerful tools that humanity has ever created.” Yet this perspective assumes AI is merely a tool to be mastered, rather than a technology that may fundamentally alter the cognitive development process that education is designed to facilitate.

The long-term consequences extend beyond individual academic performance. A generation educated with AI shortcuts may lack the foundational skills necessary for independent thought, creative problem-solving, and intellectual engagement. These are not merely academic concerns but societal ones, as democratic participation and informed citizenship require precisely the capabilities that AI-assisted education may fail to develop.

Building a Better Approach

The calculator analogy falls short because it assumes all tools serve the same purpose. AI is different. It does not just support learning; it can replace it. That difference calls for a new way of thinking.

Rather than arguing over whether AI should be allowed or banned, educators need clear strategies that separate helpful uses from those that take away learning. The focus should be on building thinking skills, not just completing tasks. Learning is a process, and the effort involved is what helps students grow.

The goal is not to make schools resistant to AI. It is to make sure AI supports learning instead of replacing it. That begins with clear guidelines and a focus on real educational value.

Here are five actions educators can take to move in that direction.

1. Design Assignments That Require Real Thinking: Avoid homework that AI can easily complete. Instead, ask students to submit drafts, notes, and revisions. Use in-class writing and oral exams to assess genuine understanding. Create assignments that rely on classroom materials, so students must stay engaged to succeed.
2. Set Clear Rules on AI Use and Explain Why: Define when AI is allowed, such as for brainstorming or research support, and when it is not, such as for final writing or problem-solving. Most importantly, explain the reasons behind these rules. Help students understand that education is about developing thinking skills, not just finishing tasks.
3. Ask Students to Show Their Thinking: Require more than just final answers. In writing, include source notes and reflections. In problem-solving, ask for step-by-step explanations. For research, collect logs that show how ideas and sources were chosen. This helps make the learning process visible and harder to fake with AI.
4. Use In-Class Activities to Check Understanding: Include more pop quizzes, discussions, and group tasks that reveal actual comprehension. Try activities like think-pair-share or short reflections at the end of class. These real-time checks show the difference between polished assignments and true understanding.
5. Teach Students to Think Critically About AI: Spend class time analyzing AI responses for mistakes, bias, and limits. Have students fact-check results and practice asking clear questions. Show examples of strong human work next to AI-generated work. Teach them how to use AI as a tool while keeping their own thinking front and center.

These strategies preserve the cognitive development that education is designed to foster while acknowledging AI’s presence in students’ lives. The goal is not to ban AI entirely, but to ensure it serves learning rather than replacing it.

The Path Forward

We can’t afford to keep using shallow comparisons that hide the real problems.

Put simply, the calculator analogy doesn’t work.

Research and classroom experience show that AI can do the thinking for students, removing the need for real learning. Calculators support thinking. AI can replace it. That difference matters.

Moving forward means we must recognize this and build educational approaches that use AI wisely, without letting it take over the learning process. If we want students to think for themselves, we need to stop comparing AI to tools that never did the thinking for them.

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Chris Hood is an AI strategist and author of the #1 Amazon Best Seller “Infailible” and “Customer Transformation,” and has been recognized as one of the Top 40 Global Gurus for Customer Experience.